Good Visual Quality Research Articles

Reversible data hiding of JPEG images based on block sorting and segmented embedding

Existing JPEG image reversible data hiding (RDH) schemes based on quantized DCT (Discrete cosine transform) modification usually use non-zero or zero AC (Alternating current) coefficients as peak points for data embedding. However, this approach tends to limit the embedding capacity or result in significant file size growth. This paper proposed an RDH scheme for JPEG images based on DCT block sorting and segmented embedding. This scheme can take into account the dual advantages of having a non-zero or zero AC coefficient as the peak point, so it has both high embedding capacity and low file growth, and good visual quality. Firstly, a new DCT block sorting method is designed, the smoothness of the block is estimated by the number of zero coefficients in the EOB (End of Block) and the fluctuation of the DC coefficient in the block, and the zero coefficients in the EOB in the block have not embedded data. Then, the sorted DCT block sequence is divided into three segments, the peak points of the front two segments are (−1, 1) and (−1, 0) respectively, and the third segment may be empty but it always remains unchanged. Finally, the dynamic allocation method is used to quickly solve the optimal segmentation point to achieve the optimal embedding performance. The experimental results show that the overall performance of this scheme is better than the existing state-of-the-art algorithms.

Lightweight image super-resolution based multi-order gated aggregation network

Recently, Transformer-based models are taken much focus on solving the task of image super-resolution (SR) due to their ability to achieve better performance. However, these models combined huge computational cost during the computing self-attention mechanism. To solve this problem, we proposed a multi-order gated aggregation super-resolution network (MogaSRN) for low-level vision based on the concept of the MogaNet that is developed for high-level vision. The concept of the MogaSRN model is based on spatial multi-order context aggregation and adaptive channel-wise reallocation with the aid of the multi-layer perceptron (MLP). In contrast to the MogaNet model, in which the resolution of each stage decreased by a factor of 2, the resolution of the MogaSRN is stayed fixed during the deep features extraction. Moreover, the structure of the MogaSRN model is built based on balancing the performance and the model complexity. We evaluated our model based on five benchmark datasets concluding that the MogaSRN model can achieve significant improvements compared to the state-of-the-art. Moreover, our model shows the good visual quality and accuracy of the reconstruction. Finally, our model has 3.7 × faster runtime at the scale of × 4 compared to LWSwinIR with better performance.

Multiparametric dynamic whole-body PSMA PET/CT using [68Ga]Ga-PSMA-11 and [18F]PSMA-1007

BackgroundRoutine prostate-specific membrane antigen (PSMA) positron emission tomography (PET) performed for primary staging or restaging of prostate cancer patients is usually done as a single static image acquisition 60 min after tracer administration. In this study, we employ dynamic whole-body (D-WB) PET imaging to compare the pharmacokinetics of [68Ga]Ga-PSMA-11 and [18F]PSMA-1007 in various tissues and lesions, and to assess whether Patlak parametric images are quantitative and improve lesion detection and image readability.MethodsTwenty male patients with prostate cancer were examined using a D-WB PSMA PET protocol. Ten patients were scanned with [68Ga]Ga-PSMA-11 and ten with [18F]PSMA-1007. Kinetic analyses were made using time-activity curves (TACs) extracted from organs (liver, spleen, bone, and muscle) and lesions. For each patient, three images were produced: SUV + Patlak parametric images (Ki and DV). All images were reviewed visually to compare lesion detection, image readability was quantified using target-to-background ratios (TBR), and Ki and DV values were compared.ResultsThe two PSMA tracers exhibited markedly different pharmacokinetics in organs: reversible for [68Ga]Ga-PSMA-11 and irreversible for [18F]PSMA-1007. For both tracers, lesions kinetics were best described by an irreversible model. All parametric images were of good visual quality using both radiotracers. In general, Ki images were characterized by reduced vascular signal and increased lesion TBR compared with SUV images. No additional malignant lesions were identified on the parametric images.ConclusionD-WB PET/CT is feasible for both PSMA tracers allowing for direct reconstruction of parametric Ki images. The use of multiparametric PSMA images increased TBR but did not lead to the detection of more lesions. For quantitative whole-body Ki imaging, [18F]PSMA-1007 should be preferred over [68Ga]Ga-PSMA-11 due to its irreversible kinetics in organs and lesions.

HYBRID SCHEMES BASED ON WAVELET TRANSFORM AND CONVOLUTIONAL AUTO-ENCODER FOR IMAGE COMPRESSION

In recent years, image compression techniques have received a lot of attention from researchers as the number of images at hand keep growing. Digital Wavelet Transform is one of them that has been utilized in a wide range of applications and has shown its efficiency in image compression field. Moreover, used with other various approaches, this compression technique has proven its ability to compress images at high compression ratios while maintaining good visual image quality. Indeed, works presented in this paper deal with mixture between Deep Learning algorithms and Wavelets Transformation approach that we implement in different color spaces. In fact, we investigate RGB and Luminance/Chrominance YCbCr color spaces to develop three image compression models based on Convolutional Auto-Encoder (CAE). In order to evaluate the models’ performances, we used 24 raw images taken from Kodak database and applied the approaches on every one of them and compared achieved experimental results with those obtained using standard compression method. We draw this comparison in terms of performance parameters: Structural Similarity Index Metrix SSIM, Peak Signal to Noise Ratio PSNR and Mean Square Error MSE. Reached results indicates that with proposed schemes we gain significate improvement in distortion metrics over traditional image compression method especially SSIM parameter and we managed to reduce MSE values over than 50%. In addition, proposed schemes output images with high visual quality where details and textures are clear and distinguishable.

Visual Quality Indicators with Multifocal and Dual-Focus Soft Contact Lenses for Myopia Control

Purpose. The purpose of this study was to determine and compare visual quality indicators in eyes wearing multifocal center-distance, and dual-focus soft contact lenses that are specifically designed for the purpose of myopia progression management, as well as single-vision soft contact lenses. Material and Methods. Visual quality indicators of 34 eyes of healthy, young myopic adults ages 20 to 35 were determined. Non-cycloplegic measurements were conducted without contact lenses (baseline) and while subjects wore soft multi- focal center-distance soft contact lenses (ArtMost SoftOK SMR and SEED 1-day Pure UP Multistage daily disposable), dual-focus soft contact lenses (CooperVision MiSight 1 Day), and single-vision soft contact lenses (iLens Aqua Bi-weekly). In this study, the lenses were referred to as SoftOK, Pure UP, MiSight, and iLens. The measured and analyzed visual quality indicators included high-contrast distance and near visual acuity, stereopsis, accommodative amplitude, accommo- dative response, spherical aberration, and horizontal coma. Results. High-contrast distance and near visual acuities, accommodative responses, and stereopsis values achieved with the SoftOK, Pure UP, and MiSight contact lenses werecomparable to those achieved with the iLens single-vision soft contact lenses and to baseline values. Accommodative amplitude was slightly reduced with the MiSight contact lens and spherical aberration was significantly higher with the SoftOK lens compared to the other lenses. Both findings had statistical significance (P = 0.047 and P < 0.001, respec- tively). Horizontal coma, most likely resulting from slight lens decentration, was higher and more variable with the SoftOK lens compared to the other lenses, although no statistical significance was determined. Conclusion. Dual-focus and multifocal center-distance soft contact lenses allow for good visual quality, especially clear vision at distance and near. Small differences in accommoda- tive amplitude and spherical aberration were found between lens designs, however the clinical impact requires further investigation. Keywords myopia management, soft multifocal contact lens, visual quality indicators, spherical aberration, accommodative amplitude

Invertible Privacy-Preserving Adversarial Reconstruction for Image Compressed Sensing

Since the advent of compressed sensing (CS), many reconstruction algorithms have been proposed, most of which are devoted to reconstructing images with better visual quality. However, higher-quality images tend to reveal more sensitive information in machine recognition tasks. In this paper, we propose a novel invertible privacy-preserving adversarial reconstruction method for image CS. While optimizing the quality, the reconstructed images are made to be adversarial samples at the moment of generation. For semi-authorized users, they can only obtain the adversarial reconstructed images, which provide little information for machine recognition or training deep models. For authorized users, they can reverse adversarial reconstructed images to clean samples with an additional restoration network. Experimental results show that while keeping good visual quality for both types of reconstructed images, the proposed scheme can provide semi-authorized users with adversarial reconstructed images with a very low recognizable rate, and allow authorized users to further recover sanitized reconstructed images with recognition performance approximating that of the traditional CS.

Reversible data hiding based on automatic contrast enhancement using histogram expansion

A lot of Reversible Data Hiding (RDH) methods aim to generate a stego image infinitely approaches the original image while the quality of the original image is leaved out of consideration. Juxtaposed with a plain image, a contrast enhanced version always improves the user experience significantly. Reversible Data Hiding with Contrast Enhancement (RDHCE) enhances the stego image contrast combined with its payloads and enables the cover image to be regained accurately after the payloads have been extracted. This study presents a novel RDHCE method using histogram expansion. First, a new local histogram selecting strategy is proposed to improve the contrast of the whole image. Meanwhile, the global average brightness is used as a reference to determine the shifting direction of the local histogram to prevent the image from being over-enhanced. Moreover, the contrast can be improved adaptively when a reasonable number of data is embedded at the selected embedding points. Experimental results show that, with a given payload, the proposed method achieves better contrast and maintains good visual quality compared with state-of-the-arts.

Effects of three methods for correction of low-degree against-the-rule corneal astigmatism during cataract surgery

Objective: To compare the clinical effects of and visual quality after correction of low-degree against-the-rule (ATR) corneal astigmatism by implantation of an astigmatism-corrected intraocular lens (IOL), femtosecond laser release and manual release in cataract surgery. Methods: It was a prospective cohort study. A total of 120 patients (120 eyes) with cataract combined with low-degree ATR corneal astigmatism diagnosed in Chongqing Aier Mega Eye Hospital from December 2017 to October 2020 were included and divided into 3 groups, each with 40 patients, according to their own selections of astigmatism correction methods during cataract surgery. In the astigmatism-corrected IOL group, phacoemulsification for cataract extraction combined with toric IOL implantation was performed. In the femtosecond laser release group, astigmatic keratotomy using a femtosecond laser was combined. In the manual release group, a limbal relaxing incision was made. Uncorrected distance visual acuity (UDVA) and corneal astigmatism were measured before surgery. At 3 months and 1 year after surgery, UDVA and best-corrected distance visual acuity were examined, as well as whole eye residual astigmatism by ARK-1, corneal astigmatism by the IOLMaster 500, whole eye high order aberration (HOA) and modulation transfer function (MTF) by the iTrace visual function analyzer. Analysis of variance was used for the comparison of data in a normal distribution. Repeated measures were used for the comparison within groups. The rank sum test was used for the comparison of data that were not normally distributed. Results: Of the 120 patients, 100 patients (100 eyes), including 44 males and 56 females, with an age of (66.48±6.20) years, completed the follow-up. Among the three groups, the differences were not statistically significant in terms of gender distribution, age, preoperative corneal astigmatism, UDVA and spherical equivalent of the IOL (all P>0.05). At 3 months and 1 year after surgery, the UDVA was significantly better than that before surgery in each group (Z=5.18, 5.04, 4.98, 4.99, 4.90, 4.89; all P<0.001). At the two time points, the differences in the whole eye residual astigmatism among the three groups were statistically significant (H=30.69, 31.23; both P<0.001). At 3 months, the whole eye residual astigmatism in the astigmatism-corrected IOL group was lower than that in the other two groups. At 1 year, the residual astigmatism in the astigmatism-corrected IOL group [0.25(0.00, 0.50) D] was also lower compared to that in the femtosecond laser release group [0.50(0.50, 0.75) D] and the manual release group [0.75(0.50, 0.75) D] (Z=-3.71, -5.18, -3.94, -5.15; all P<0.001). The differences in the HOA at 3 months and 1 year among the three groups were statistically significant (H=36.30, 34.38; both P<0.001). The HOA in the astigmatism-corrected IOL group was significantly higher than that in the other two groups at the two time points (Z=5.01, 4.73, 5.31, 5.27; all P<0.001). At 3 months and 1 year, the differences in the MTF value among the three groups were also statistically significant (H=30.02, 29.92; both P<0.001), and the MTF value in the femtosecond laser release group was significantly higher than that in the other two groups (Z=4.61, 4.67, 4.66, 4.69; all P<0.001). Conclusions: All the three astigmatism correction methods used at the time of cataract surgery can effectively correct low-degree ATR corneal astigmatism. The residual astigmatism in the whole eye after astigmatism-corrected IOL implantation is small and stable, while the HOA after release using the femtosecond laser is low with good visual quality.

Robust Method for Embedding an Image inside Cover Image based on Least Significant Bit Steganography

According to the enormous evolution of the internet and communications, the security of private or sensitive information has become the important issue. The private information can be passed between a sender and a receiver with high security using Cryptography and Steganography. By the cryptography, as the information can be secured with the cipher key for encryption. By the Steganography, the secret information can hide within usual data such as images, videos, audios. In this paper we proposed the robust method that includes two phases. The first phase consists of two stages. In the first stage we encrypt a secret image using encryption algorithm in order of increasing security of information. In the second stage, we complete the first stage for embedding the most significant bits (MSB) of the encrypted image into the least significant bits(LSB) of the cover image for instituting the stego image. The second phase is the obverse of the first phase, where, the encrypted image is retrieved from the stego image and then, decrypted process construct the secret image. The proposed method is efficient in terms of security compare with the other methods. Where, both encryption and embedding algorithms have an efficient role for embedding the secret image and preserving the good visual quality of stego images. Furthermore, extraction algorithms obtained better and faster results to a restoration of the secret image.

Investigation on principles for cost assignment in motion vector-based video steganography

Cost assignment in the motion vector domain remains a research focus in video steganography. Recent studies in image steganography have summarized many principles for cost assignment and achieved good results. But the basic principles for cost assignment in motion vector-based video steganography have not been fully discussed yet. Firstly, this paper proposes three principles for cost assignment in the motion vector domain, including the principle of local optimality, non-consistency in the block group, and complexity priority. Secondly, three corresponding novel practical distortion functions were designed according to the three principles. Finally, a joint distortion function is constructed based on all three principles to increase overall performance. The experimental results show that not only the three independent distortion functions can effectively resist the corresponding steganalysis attacks, but the final joint distortion can resist the three steganalysis features simultaneously. In addition, it can obtain good visual quality and coding efficiency, which can be applied to practical scenarios.

Attributes of a Mobile App as Perceived by Field Veterinarians: Case of Pig Master

his study presents the perceived characteristics of pig master, a mobile app developed as a Continuing Veterinary Education (CVE) tool for veterinarians. The CVE programmes are being taken up by various institutions in India and it was observed that many of the field veterinarians are not able to attend the regular CVE programmes for obvious reasons, for whom ICT tools like mobile devices can be useful. In this context, veterinarians’ perception of the mobile application on pig farming developed after the need assessment was assessed. The study was carried out with the veterinarians of the State Department of Animal Husbandry (SDAH), Andhra Pradesh. A sample of 91 field veterinarians was studied to whom Android Package on pig farming and questionnaires were sent. The ‘pig master’ mobile application was found to have good visual quality, more credible, effective in arousal of curiosity and was with high information coverage along with user-friendliness. Moreover, the app was also found with remarkable utility and helpful in decision-making as expressed by the majority of the field veterinarians. This study emphasizes the need of making CVE programmes effective by using digital media towards enrichment of knowledge of veterinarians.

Medical image fusion using convolutional neural network

Medical image fusion methods combine medical pictures from many morphologies to improve the accuracy and reliability of medical diagnoses, and they are becoming more significant in a variety of clinical applications. This research introduces a convolutional neural network (CNN) based medical image fusion approach to create a fused picture with good visual quality and clear structural details. To generate a weight map, the proposed technique employs a trained Siamese convolutional network to fuse the pixel activity information of source pictures. Meanwhile, the original picture is decomposed using a contrast pyramid. Source pictures are combined using distinct spatial frequency bands and a weighted fusion operator. The suggested fusion method can successfully maintain the exact structural information of source pictures and generate excellent human visual effects, according to the findings of comparison trials.

A Robust Steganographic Algorithm based on Linear Fractional Transformation and Chaotic Maps

The fundamental objectives of a steganographic technique are to achieve both robustness and high-capacity for the hidden information. This paper proposes a steganographic algorithm that satisfies both of these objectives, based on enhanced chaotic maps. The algorithm consists of two phases. In the first phase, a cryptographic substitution box is constructed using a novel fusion technique based on logistic and sine maps. This technique overcomes existing vulnerabilities of chaotic maps, such as frail chaos, finite precision effects, dynamical degradation, and limited control parameters. In the second phase, a frequency-domain-based embedding scheme is used to transform the secret information into ciphertext by employing the substitution boxes. The statistical strength of the algorithm is assessed through several tests, including measures of homogeneity, correlation, mean squared error, information entropy, contrast, peak signal-to-noise ratio, energy, as well as evaluations of the algorithm's performance under JPEG compression and image degradation. The results of these tests demonstrate the algorithm's robustness against various attacks and provide evidence of its high-capacity for securely embedding secret information with good visual quality.

ENHANCEMENT OF SECURED DATA TRANSMISSION USING n*3 INCOMPREHENSIBLE STEGO FILES BASED ON LS, SL, AND LC ALGORITHMS

In this paper, security of covert communication is increased by using &lt;i&gt;n&lt;/i&gt;&lt;sup&gt;*&lt;/sup&gt;3 incomprehensible stego files based on the novel algorithms, which are logical and statistical (LS), split logical (SL), and logical concealing (LC). Generally, cryptography and steganography techniques are used to achieve a secured data transmission. Cryptography is used to generate the "ciphertext" and steganography is used to produce the understandable stego image. The results of these two techniques alert the intruder to the fact that secret information is being exchanged. To overcome this drawback, this paper generates n*3 incomprehensible stego files with four levels of security using covert data and a container (cover) image. The main novelty of the proposed framework is that it provides multilevel security for data transmission by converting understandable stego images into non-understandable (incomprehensible) stego files. The LS encryption algorithm generates the lesser length of ciphertext with the input of covert data. The steganography generates a good visual quality of an understandable stego image by using discrete framelet transform (DFT) and random pixel embedding (RPE) techniques. Finally, the SL and LC algorithms produce &lt;i&gt;n&lt;/i&gt;&lt;sup&gt;*&lt;/sup&gt;3 incomprehensible stego files using the understandable stego image. These stego files are incomprehensible, meaningless, and invisible in nature. The experimental results have shown that the incomprehensible stego files improve the payload capacity, quality metrics (peak signal-to-noise ratio, correlation, and number of pixels change in rate), and also four levels of security to the secret data. It is also able to face the various steganalysis attacks, such as files deletion, data deletion, and data modification.

Image Scaling by de la Vallée-Poussin Filtered Interpolation

We present a new image scaling method both for downscaling and upscaling, running with any scale factor or desired size. The resized image is achieved by sampling a bivariate polynomial which globally interpolates the data at the new scale. The method’s particularities lay in both the sampling model and the interpolation polynomial we use. Rather than classical uniform grids, we consider an unusual sampling system based on Chebyshev zeros of the first kind. Such optimal distribution of nodes permits to consider near-best interpolation polynomials defined by a filter of de la Vallée-Poussin type. The action ray of this filter provides an additional parameter that can be suitably regulated to improve the approximation. The method has been tested on a significant number of different image datasets. The results are evaluated in qualitative and quantitative terms and compared with other available competitive methods. The perceived quality of the resulting scaled images is such that important details are preserved, and the appearance of artifacts is low. Competitive quality measurement values, good visual quality, limited computational effort, and moderate memory demand make the method suitable for real-world applications.

Perceptual quality assessment for fine-grained compressed images

Recent years have witnessed the rapid development of image storage and transmission systems, in which image compression plays an important role. Generally speaking, image compression algorithms are developed to ensure good visual quality at limited bit rates. However, due to the different compression optimization methods, the compressed images may have different levels of quality, which needs to be evaluated quantificationally. Nowadays, the mainstream full-reference (FR) metrics are effective to predict the quality of compressed images at coarse-grained levels (the bit rates differences of compressed images are obvious), however, they may perform poorly for fine-grained compressed images whose bit rates differences are quite subtle. Therefore, to better improve the Quality of Experience (QoE) and provide useful guidance for compression algorithms, we propose a full-reference image quality assessment (FR-IQA) method for compressed images of fine-grained levels. Specifically, the reference images and compressed images are first converted to YCbCr color space. The gradient features are extracted from regions that are sensitive to compression artifacts. Then we employ the Log-Gabor transformation to further analyze the texture difference. Finally, the obtained features are fused into a quality score. The proposed method is validated on the fine-grained compression image quality assessment (FGIQA) database, which is especially constructed for assessing the quality of compressed images with close bit rates. The experimental results show that our metric outperforms mainstream FR-IQA metrics on the FGIQA database. We also test our method on other commonly used compression IQA databases and the results show that our method obtains competitive performance on the coarse-grained compression IQA databases as well.

Brain activity during shadowing of audiovisual cocktail party speech, contributions of auditory–motor integration and selective attention

Selective listening to cocktail-party speech involves a network of auditory and inferior frontal cortical regions. However, cognitive and motor cortical regions are differentially activated depending on whether the task emphasizes semantic or phonological aspects of speech. Here we tested whether processing of cocktail-party speech differs when participants perform a shadowing (immediate speech repetition) task compared to an attentive listening task in the presence of irrelevant speech. Participants viewed audiovisual dialogues with concurrent distracting speech during functional imaging. Participants either attentively listened to the dialogue, overtly repeated (i.e., shadowed) attended speech, or performed visual or speech motor control tasks where they did not attend to speech and responses were not related to the speech input. Dialogues were presented with good or poor auditory and visual quality. As a novel result, we show that attentive processing of speech activated the same network of sensory and frontal regions during listening and shadowing. However, in the superior temporal gyrus (STG), peak activations during shadowing were posterior to those during listening, suggesting that an anterior–posterior distinction is present for motor vs. perceptual processing of speech already at the level of the auditory cortex. We also found that activations along the dorsal auditory processing stream were specifically associated with the shadowing task. These activations are likely to be due to complex interactions between perceptual, attention dependent speech processing and motor speech generation that matches the heard speech. Our results suggest that interactions between perceptual and motor processing of speech relies on a distributed network of temporal and motor regions rather than any specific anatomical landmark as suggested by some previous studies.

Establishment and development of ornamental grasses on green roofs and living walls

Ornamental grasses are often used in gardens to improve biodiversity and as additional aesthetical resources. However, their use in green roofs (GR) and living walls (LW) is not so widespread and it has not been studied extensively. The aim of this work is to assess the performance of seven grass species (Imperata cylindrica ‘Red Baron’, Acorus gramineus, Stipa tenuissima ‘Pony Fails’, Carex flagellifera ‘Bronzita’, Carex oshimensis ‘Evergold’, Uncinia rubra ‘Everflame’ and Miscanthus sinensis) for their use in GR and LW. The growth of the plants was evaluated (i.e. biomass production, dimensions), as well as their visual quality and survival. C. flagellifera and C. oshimensis showed coverage levels greater than 75% and good visual quality, while A. gramineus reached 55–60%. I. cylindrica and M. sinensis showed coverages slightly below 50% in the LW, however, both performed well in the GR, though with a lower visual quality. U. rubra did not develop well, reaching the lowest coverage (below 45%) but maintaining a high visual quality. S. tenuissima also attained low coverage in the LW and presented high mortality, especially in the GR. In LW, C. oshimensis stood out in flowering, while S. tenuissima showed the highest flowering rate in GR. The species should be selected considering their characteristics and performance in order to achieve a correct appearance and development. Interspecific interactions are especially important in LW, as species with upward growth should be placed above species with fallen leaves, not below.

A Novel Separable Scheme for Encryption and Reversible Data Hiding

With the increasing emphasis on security and privacy, video in the cloud sometimes needs to be stored and processed in an encrypted format. To facilitate the indexing and tampering detection of encrypted videos, data hiding is performed in encrypted videos. This paper proposes a novel separable scheme for encryption and reversible data hiding. In terms of encryption method, intra-prediction mode and motion vector difference are encrypted by XOR encryption, and quantized discrete cosine transform block is permutated based on logistic chaotic mapping. In terms of the reversible data hiding algorithm, difference expansion is applied in encrypted video for the first time in this paper. The encryption method and the data hiding algorithm are separable, and the embedded information can be accurately extracted in both encrypted video bitstream and decrypted video bitstream. The experimental results show that the proposed encryption method can resist sketch attack and has higher security than other schemes, keeping the bit rate unchanged. The embedding algorithm used in the proposed scheme can provide higher capacity in the video with lower quantization parameter and good visual quality of the labeled decrypted video, maintaining low bit rate variation. The video encryption and the reversible data hiding are separable and the scheme can be applied in more scenarios.

Canning quality of popular common bean germplasm in Eastern and Central Africa

Common bean (Phaseolus vulgaris L.) genotypes popular in eastern and central Africa were evaluated to determine their suitability for the canning industry. The genotypes were planted at the National Agricultural Research Laboratories (NARL), Kawanda-Uganda in the second rainy seasons (July-September) of 2015, 2016 and off season of 2017 (November- February). Two samples per genotype were evaluated at the canning facilities at Kawanda and Michigan State University (MSU) using a protocol based on home canning. One sample per genotype from the 2017 harvest was evaluated at Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre (AAFC-LRDC) using the industry canning protocol. Data (n=134) was collected on seed moisture content, dry and soaked bean weight, hydration coefficient (HC) and visual quality, including colour retention, appearance, brine clarity, bean splitting and freedom starch/clumps on replicated samples. Additional data on unreplicated samples were collected on 100-seed weight, seed solids for canning, hydration coefficient after soaking (HCS), hydration coefficient after blanching (HCB), drain weight (%), matting, appearance, seed color, texture, and cooking quality traits including hard seed and partially hydrated seed (%) and HC after cooking. Analysis of variance of data from MSU and Kawanda showed significant (P≤0.01) differences among genotypes for the assessed parameters. Majority of the genotypes expressed good soaking ability considering that their HC were above the 1.8 recommended for canning and 28% combined the two mentioned traits with good overall canning quality visual rating. Apart from 26, all other varieties had good HC based on data from Canada. About 24% of genotypes belonging to various market classes consistently combined this trait with good visual quality. The most outstanding genotypes based on these traits included SAB659 (red mottled), MAC44 (red mottled), NABE21 (cream), NABE12C (cream) and VAX5 (cream), KK8 (red mottled), Bihogo (yellow) and VAX4 (black). These genotypes were superior to the white beans: MEXICO 142, Awash1, and Awash Melka, that were considered as high-quality controls. Results indicated that genotypes of diverse backgrounds, with good canning quality traits exist among the currently utilised varieties and breeding lines. This diversity could be exploited for breeding and varietal promotion in the canning industry. Key words: Common bean, canning, hydration coefficient, visual quality, drained weight