Red Channel Research Articles

Identification of Greenish Soybean Seeds through Image Processing, under Different Types of Lighting

A high occurrence of greenish soybean seeds in crops is an issue, these types of seeds have low physiological quality, which can generate seedlings with anomalies, if destined for processing in industries, the presence of chlorophyll is undesirable, requiring additional processes for its removal. This work aimed to evaluate the differentiation of mature and greenish soybean seeds, illuminated with red laser, green laser, red LED, and fluorescent lamp, using image processing. Images of mature and greenish soybean seeds were captured at a resolution of 340x480 pixels, illuminated with red laser, green laser, red LED, and fluorescent lamp. Subsequently, the averages of the gray levels of each image were obtained in the red, green, blue channels and in images converted to grayscale 8-bit. The data were submitted to tests of variance after gray level for image classification. And a validation presented results of 97% of hits for red laser, 94% for fluorescent light and 93.5% for red LED, all in red channel. Keywords: seed classification, agricultural automation, soybean seed quality, computer vision

A Secure and High Capacity Image Steganography Approach Using Huffman Coding and RSA Encryption

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), and comparison to findings from related prior efforts.

Dual-source gramian angular field method and its application on fault diagnosis of drilling pump fluid end

Under complex drilling working conditions, it is difficult to completely describe the working state of the drilling pump fluid end with a single-source signal to achieve a high fault diagnosis accuracy. This paper proposes to use dual-source signals (vibration signal and strain signal) to describe the working state of the fluid end. Especially, a dual-source gramian angular field (DS-GAF) method is proposed to fuse vibration-strain signals to provide more fault information. In DS-GAF method, the dual-source signal is converted to points in spherical coordinates, and the arccosine of the normalized amplitude of the two signals is assumed as the polar angle and the azimuthal angle, respectively. Three DS-GAF matrices are generated with the position of the points. These three matrices are respectively encoded as three colors (red, green, and blue) channels of the image to achieve signal fusion. A fault diagnosis method based on DS-GAF and ResNet for the drilling pump fluid end is proposed to improve the fault diagnosis accuracy under multiple working conditions. First, by the DS-GAF method, the vibration-strain signals of the fluid end are fused and converted into a fault diagnosis image dataset. Second, a fault diagnosis model based on ResNet is established and the effect of batch size on the performance of the fault diagnosis model is discussed. Finally, fault diagnosis experiments are carried out on the proposed fault diagnosis model and its performance is investigated. The results show that the diagnosis method proposed in this paper has the highest diagnostic accuracy of 98.97% for nine fault types under multiple operating conditions, with a maximum improvement of 18.91% compared to the original GAF method. The DS-GAF method for signal fusing proposed in this paper not only improves the accuracy of fluid end diagnosis, but also provides a reference for the signal-fusion diagnosis of other equipment.

DFFA-Net: A Differential Convolutional Neural Network for Underwater Optical Image Dehazing

This paper proposes DFFA-Net, a novel differential convolutional neural network designed for underwater optical image dehazing. DFFA-Net is obtained by deeply analyzing the factors that affect the quality of underwater images and combining the underwater light propagation characteristics. DFFA-Net introduces a channel differential module that captures the mutual information between the green and blue channels with respect to the red channel. Additionally, a loss function sensitive to RGB color channels is introduced. Experimental results demonstrate that DFFA-Net achieves state-of-the-art performance in terms of quantitative metrics for single-image dehazing within convolutional neural network-based dehazing models. On the widely-used underwater Underwater Image Enhancement Benchmark (UIEB) image dehazing dataset, DFFA-Net achieves a peak signal-to-noise ratio (PSNR) of 24.2631 and a structural similarity index (SSIM) score of 0.9153. Further, we have deployed DFFA-Net on a self-developed Remotely Operated Vehicle (ROV). In a swimming pool environment, DFFA-Net can process hazy images in real time, providing better visual feedback to the operator. The source code has been open sourced.

A novel activatable fluorescent probe for revealing the dynamic of esterase and viscosity during ferroptosis and DILI

Esterase, a hydrolase, is present in a vast variety of animals, plants, and microbes. It has the potential to promote the hydrolysis of diverse esters while also could function as a valid indicator for assessing cell health. Besides, viscosity is a crucial metric for determining the smooth flow state of various biological macromolecules including proteins, polysaccharides, and lipids in the biological system, which is essential for intracellular signaling and interplay among multiple biological elements. Nevertheless, investigating the relationship between esterase activity, and viscosity in several relevant physiological and pathological processes remains challenging, owing to a lack of an appropriate tool. Herein, EaV is a unique multifunctional fluorescent probe that could measure local microviscosity and esterase in live cells via green and red channels at the same time. The utility of EaV for cell imaging was proven by measuring the esterase and viscosity changes in different cell states. More notably, we studied the changes in esterase and viscosity during erastin-induced ferroptosis, detecting for the first time a considerable reduction in esterase activity and an evident elevation in viscosity. In addition, EaV was used to image the changes of viscosity and esterase in the APAP-induced liver damage model. This fluorescence imaging tool revealed a flexible platform capable of highlighting variations of esterase and viscosity in many cellular processes and was also meaningful in further actually applied in more related early diagnosis and medical intervention.

Airglow observed by a full-band imager together with multi-instruments in Taiwan during nighttime of 1 November 2021

This study demonstrates an innovative approach of using a full-band chromatic all-sky imager, routinely operational for monitoring sky conditions at Lulin observatory (23.5°N, 120.9°E, 12.5° N magnetic latitude), Taiwan, to investigate equatorial plasma bubbles (EPBs). Distinct north–south aligned EPB depletions are identified by decomposing the color-scale images to respective red (centered at 630 nm) and green (520 nm) channels, where blue channel (470 nm) helps for background suppression. The intense EPBs, drifting eastwards at 60–100 m/s velocity, are also associated with reduced total electron content (TEC) values; increased ROTI (rate of TEC index); remarkable range spread-F; and prominent fluctuations in Doppler frequency shifts as well as FORMOSAT-7/COSMIC-2 electron density/S4 scintillation profiles. The results show that a full-band chromatic imager offers a cost-effective alternative to investigate the EPBs usually detected in OI 630.0 and 557.7 nm airglow emissions.

Direct Determination of the Aluminum Content in Antiperspirants Using Digital Image Colorimetry

AbstractIn this work a dilute‐and‐shoot procedure using digital image colorimetry (DIC) was evaluated for the determination of aluminum in antiperspirants. Derivatization was performed by means of the reaction between Al(III) and Alizarin Red S (ARS) reagent. Digital images were acquired using a table scanner and the average values for red, green and blue channels (RGB) were obtained. Optimal conditions were set at pH=4.5, ARS concentrations 10‐fold higher than Al(III) and using the G channel. The method presented linearity in the 2.0–10.0 mg L−1 range, the limit of detection (LOD) was 1.1 mg L−1 and precision was better than 2.55 %. Accuracy was checked by the analysis of spiked samples at 2.0 and 4.0 mg L−1 Al(III), and good recoveries (82.6–117.5 %) were obtained. Eight samples of roll‐on antiperspirants were analyzed by the proposed colorimetric method and the well‐stablished flame atomic absorption spectrometry (FAAS) comparative method. The obtained results were not statistically different at 95 % confidence level. An analytical greenness assessment was performed for both methods and the procedure based on digital image colorimetry was proven to be a greener approach due to miniaturization, low sample consumption, least amount of waste and high sample throughput.

Unveiling the Crucial Roles of O2•- and ATP in Hepatic Ischemia-Reperfusion Injury Using Dual-Color/Reversible Fluorescence Imaging.

Hepatic ischemia-reperfusion injury (HIRI) is mainly responsible for morbidity or death due to graft rejection after liver transplantation. During HIRI, superoxide anion (O2•-) and adenosine-5'-triphosphate (ATP) have been identified as pivotal biomarkers associated with oxidative stress and energy metabolism, respectively. However, how the temporal and spatial fluctuations of O2•- and ATP coordinate changes in HIRI and particularly how they synergistically regulate each other in the pathological mechanism of HIRI remains unclear. Herein, we rationally designed and successfully synthesized a dual-color and dual-reversible molecular fluorescent probe (UDP) for dynamic and simultaneous visualization of O2•- and ATP in real-time, and uncovered their interrelationship and synergy in HIRI. UDP featured excellent sensitivity, selectivity, and reversibility in response to O2•- and ATP, which rendered UDP suitable for detecting O2•- and ATP and generating independent responses in the blue and red fluorescence channels without spectral crosstalk. Notably, in situ imaging with UDP revealed for the first time synchronous O2•- bursts and ATP depletion in hepatocytes and mouse livers during the process of HIRI. Surprisingly, a slight increase in ATP was observed during reperfusion. More importantly, intracellular O2•-─succinate dehydrogenase (SDH)─mitochondrial (Mito) reduced nicotinamide adenine dinucleotide (NADH)─Mito ATP─intracellular ATP cascade signaling pathway in the HIRI process was unveiled which illustrated the correlation between O2•- and ATP for the first time. This research confirms the potential of UDP for the dynamic monitoring of HIRI and provides a clear illustration of HIRI pathogenesis.

An unsolvable pixel reduced authentication method for color images with grayscale invariance

This paper introduces an advanced grayscale-invariant authentication method for color images. Prior work directly utilizes the most significant bits (MSBs) of the red and blue channels for authentication code generation and embeds these codes into the least significant bits (LSBs). Concurrently, the green channel is adjusted to sustain consistent grayscale values. However, this direct utilization of MSBs often leads to a decline in image quality and results in a significant number of unsolvable pixels. To address these challenges, we present a new approach specifically designed to combat the deterioration of image quality and the prevalence of unsolvable pixels. In our method, we propose the MSB alteration (MSBA) technique, which modifies the MSBs of the red and blue channels to generate authentication codes with minimal distortion. This technique effectively reduces image distortion and the number of unsolvable pixels. Furthermore, we introduce the pixel substitution strategy (PSS) and the constraint-reduced strategy (CRS) to enhance the embedding efficiency. Experimental results demonstrate that our method outperforms prior work by converting more unsolvable pixels to solvable ones and achieving better detection results. Moreover, our method enhances image quality by approximately 1.5 dB, while maintaining the same embedding capacity.

Underwater image enhancement via multi-scale fusion and adaptive color-gamma correction in low-light conditions

In dark underwater areas, existing single-model underwater image enhancement methods have poor enhancement effects. We propose an underwater image enhancement method based on color correction and multi-scale fusion (CCMF). Specifically, we first design a color correction method with red channel compensation, which compensates for the red channel according to light attenuation and removes color bias. We propose a contrast enhancement method based on guided filtering to enhance edge texture details. The image is decomposed into a base layer and a detail layer in the logarithmic domain, with layered enhancement. Secondly, we propose an adaptive gamma correction method that dynamically adjusts correction parameters based on the gray image values. This approach prevents over-enhancement and effectively enhances the exposure in dark areas. We extract weight maps that represent different features from the input images and employ a multi-scale pyramid fusion technique to integrate the aforementioned feature information. This approach enables the mutual complementarity of various features and enhances the overall visual effect. Experimental results show that our method can effectively integrate the advantages of different enhancement methods, and the objective indicators of UCIQE, UIQM, and EG are better than other related state-of-the-art methods.

Influence of Chinese red culture on foreign communication under the background of big data and Internet of Things

Red culture was born in the revolutionary war era. It contains a rich revolutionary spirit and profound historical and cultural connotations. It plays a pivotal role in education, politics, economy and society, and has a crucial influence in all aspects. In this paper, based on the analysis of big data and IoT-related theories, the current issues of red culture dissemination and influence development are obtained through interviews and questionnaire surveys. In terms of red culture dissemination channels, based on big data, solutions such as establishing a digital red culture database, pinpointing demand groups and combining recommendation algorithms are proposed to improve the speed and impact of dissemination. The coordinated red culture has been improved in terms of dissemination speed, dissemination efficiency, depth of influence, number of influencers, and breadth of influence. The innovation of this paper is to study the development of red culture through big data and Internet of things technology, explore the problems existing in the development of red culture from a new perspective, and put forward corresponding strategies, which is of great innovation.

Versatile recognition of graphene layers from optical images under controlled illumination through green channel correlation method

In this study, a simple yet versatile method is proposed for identifying the number of exfoliated graphene layers transferred on an oxide substrate from optical images, utilizing a limited number of input images for training, paired with a more traditional number of a few thousand well-published Github images for testing and predicting. Two thresholding approaches, namely the standard deviation-based approach and the linear regression-based approach, were employed in this study. The method specifically leverages the red, green, and blue color channels of image pixels and creates a correlation between the green channel of the background and the green channel of the various layers of graphene. This method proves to be a feasible alternative to deep learning-based graphene recognition and traditional microscopic analysis. The proposed methodology performs well under conditions where the effect of surrounding light on the graphene-on-oxide sample is minimum and allows rapid identification of the various graphene layers. The study additionally addresses the functionality of the proposed methodology with nonhomogeneous lighting conditions, showcasing successful prediction of graphene layers from images that are lower in quality compared to typically published in literature. In all, the proposed methodology opens up the possibility for the non-destructive identification of graphene layers from optical images by utilizing a new and versatile method that is quick, inexpensive, and works well with fewer images that are not necessarily of high quality.

Evaluation of a new radiochromic film dosimeter, Gafchomic EBT4, for VMAT, SABR and HDR treatment delivery verification

Objective. To evaluate a new film for radiotherapy dosimetry, Gafchromic EBT4, compared to the current EBT3. To evaluate dose-response and verify test cases in MV external beam and HDR brachytherapy. Approach. Three lots (batches) of EBT4 and three lots of EBT3 films were calibrated at 6 MV over 0–1200 cGy range, using FilmQAPro software. Signal-to-noise of pixel value, reported dose (RD), and factors affecting dosimetry accuracy were evaluated (rotation of the film at scanning, energy response and post-exposure darkening). Both films were exposed to clinical treatment plans (VMAT prostate, SABR lung, single HDR source dwell, and ‘pseudo’ 3-channel HDR cervix brachytherapy). Film-RD was compared to TPS-calculated dose. Main results. EBT4 calibration curves had characteristics more favourable than EBT3 for radiation dosimetry, with improved signal to noise in film-RD of EBT4 compared to EBT3 (increase of average 46% in red and green channels at 500 cGy). Film rotation at scanning and post-exposure darkening was similar for the two films. The energy response of EBT4 is similar to EBT3. For all clinical case studies, EBT4 provided better agreement with the TPS-planned doses than EBT3. VMAT prostate gamma 3%/3 mm passing rate, EBT4 100.0% compared to EBT3 97.9%; SABR lung gamma 2%/2 mm, EBT4 99.6% and EBT3 97.9%; HDR cervix gamma 3%/2 mm, EBT4 97.7% and EBT3 95.0%. Significance. These results show EBT4 is superior to EBT3 for radiotherapy dosimetry validation of TPS plan delivery. Fundamental improvements in noise profile and calibration curve are reported for EBT4. All clinical test cases showed EBT4 provided equivalent or smaller difference in measured dose to TPS calculated dose than EBT3. Baseline data is presented on the achievable accuracy of film dosimetry in radiotherapy using the new Gafchromic EBT4 film.

Quantitative Assessment of Hyperpigmentation Changes in Human Skin after Microneedle Mesotherapy Using the Gray-Level Co-Occurrence Matrix (GLCM) Method.

The aim of the study was to quantitatively assess the effectiveness of microneedle mesotherapy in reducing skin discoloration. The results were analyzed using the gray-level co-occurrence matrix (GLCM) method. The skin of the forearm (7 × 7 cm) of 12 women aged 29 to 68 was examined. Microneedle mesotherapy was performed using a dermapen with a preparation containing 12% ascorbic acid. Each of the volunteers underwent a series of four microneedle mesotherapy treatments. The effectiveness of the treatment was quantified using the methods of image analysis and processing. A series of clinical images were taken in cross-polarized light before and after a series of cosmetic procedures. Then, the treated areas were analyzed by determining the parameters of the gray-level co-occurrence matrix (GLCM) algorithm: contrast and homogeneity. During image pre-processing, the volunteers' clinical images were separated into red (R), green (G) and blue (B) channels. The photos taken after the procedure show an increase in skin brightness compared to the photos taken before the procedure. The average increase in skin brightness after the treatment was 10.6%, the average decrease in GLCM contrast was 10.7%, and the average homogeneity increased by 14.5%. Based on the analysis, the greatest differences in the GLCM contrast were observed during tests performed in the B channel of the RGB scale. With a decrease in GLCM contrast, an increase in postoperative homogeneity of 0.1 was noted, which is 14.5%.

Multiplane full-color phase-only holograms generation based on iterative algorithm with a modified amplitude constraint

Depth-division multiplexing (DDM) is distinguished for generating full-color holograms. However, this method is confronted with such issues as poor quality and severe crosstalk when reconstructing multiplane color images. In this paper, we propose an improved iterative method based on Gerchberg-Saxton (GS) algorithm to generate multiplane full-color phase-only holograms (POHs), and the information of red (R), green (G), and blue (B) channels of images is recorded in three POHs, respectively. In the iterative process, we introduce an improved hologram plane constraint that consists of modified amplitudes given a static weighting factor, and display the reconstruction results for three-layer images, which ultimately improve the quality of the reconstructed images and effectively avoid the crosstalk among different color channels. And compared with GS algorithm, our method can effectively balance the reconstruction quality of three-color channels of each image. The feasibility of the method is verified by numerical simulations and optical experiments.

Drought recognition based on feature extraction of multispectral images for the soybean canopy

Drought stress is a major environmental factor in soybean growth. Accurate and rapid detection of phenotypic traits during drought condition is important for water-saving irrigation and variety selection for the drought-resistant plant. The traditional manual measurement of phenotypes is time-consuming and error-prone, thus, an accurate and rapid drought recognition method was proposed based on feature extraction of multispectral images for the soybean canopy. First, the Suinong26 soybean variety was selected as the research object. The multispectral sensor (Parrot Drone SAS, Paris, France) was used to acquire the soybean canopies' multispectral image in four channels (NIR, RED, REG, and GRE). Second, after de-noising the original image using median filtering method, the target image of the soybean canopy in the NIR channel was extracted using a thresholding segmentation algorithm. Third, the segmented image was set as an image template to perform canopy segmentation on the rest of the channel images, the soybean canopy images were obtained in the RED, REG, and GRE channels. In addition, soybean canopies' 9 vegetation indexes (NDVI, GNDVI, NDGI, RVI, DVI, GCI, RECI, RDVI, NLI) and each channel's 7 texture features (mean, standard deviation, smoothness, third moment, information entropy, average gradient, fractal dimension) were calculated by using image fusion and processing technologies. Finally, based on the 37-dimensional features of the extracted multispectral images of the soybean canopy, a drought recognition model was established using a support vector machine (SVM) with a radial basis as the kernel function. The models' recognition accuracy reached 96.87%, and the running time was only 0.493441 s. The proposed model has improved the recognition accuracy by 8.33% on average compared with Genetic Algorithm-Backpropagation (GA-BP) neural network, radial basis neural network (RBF) and random forest (RF) method. The proposed method can provide a theoretical basis and technical support for precise regulation and scientific decision-making of breeding and cultivation management for drought-resistant soybean varieties.

LED-Based Desktop Analyzer for Fat Content Determination in Milk.

In dairy, there is a growing request for laboratory analysis of the main nutrients in milk. High throughput of analysis, low cost, and portability are becoming critical factors to provide the necessary level of control in milk collection, processing, and sale. A portable desktop analyzer, including three light-emitting diodes (LEDs) in the visible light region, has been constructed and tested for the determination of fat content in homogenized and raw cow's milk. The method is based on the concentration dependencies of light scattering by milk fat globules at three different wavelengths. Univariate and multivariate models were built and compared. The red channel has shown the best performance in prediction. However, the joint use of all three LED signals led to an improvement in the calibration model. The obtained preliminary results have shown that the developed LED-based technique can be sufficiently accurate for the analysis of milk fat content. The ways of its further development and improvement have been discussed.

DOSE MAP BLOOD IRRADIATOR DOSIMETRY SYSTEM: CUSTOMIZED BLOOD EQUIVALENT PHANTOM AND GAFCHROMIC EBT-XD FILM

Blood irradiation is done to sterilize and cease donor T-lymphocytes functionality to avoid Transfusion Associated-Graft Versus Host Disease (TA-GVHD). Dose mapping is the primary means of ensuring that the irradiation process is being conducted correctly. The aim of this study is to measure the minimum, maximum and central absorbed gamma radiation dose delivered at the newly customized blood equivalent phantom using a Gafchromic EBT-XD film. A Gammacell 3000 Elan Blood Irradiator with Cesium-137 source was used. To obtain the dose calibration curves, the films were placed at the center of a phantom and irradiated with the dose range from 5 Gy to 35 Gy with one unirradiated film as a control. The dose calibration curve was plotted using red, green and blue channels. While, for the dose mapping measurement, the irradiation exposure of 9.03 minutes was used to deliver a central dose of 25 Gy to the film. The response of the film will be compared with the GC Dose Mapping Report 2022 which used a water equivalent medium as a phantom. For the calibration curve, the red channel of the film was utilized in this study as it had a higher signal than the other channel. The doses obtained at central, minimum and maximum using EBT-XD film with customized blood equivalent phantom were in agreement with that obtained from GC Dose Mapping Report 2022 to be within ±7.6%, ±8.51% and ±9.95% respectively. We concluded that the customized blood equivalent phantom together with EBT-XD film has a potential to map the dose in blood irradiator accurately. The doses obtained from EBT-XD film were in the range of doses needed to inhibit the proliferation of the T-lymphocytes with central, minimum and maximum doses were 26.9 Gy, 17.2 Gy and 35.7 Gy respectively.

Adaptive rule-based colour component weight assignment strategy for underwater video enhancement

ABSTRACT Images and videos collected in an underwater environment often have low contrast, blur, and colour cast due to two significant sources of distortion; light scattering and absorption. In an underwater image/video, suspended particles attenuate red and blue components more than green channels. This article presents two adaptive weight allocation strategies based on rule assignment for red, green, and blue channels. Firstly, an improved balanced contrast enhancement technique (IBCET) is proposed using an adaptive contrast enhancement scheme based on colour component weight assignment. Secondly, a modified fuzzy contrast enhancement technique which obtains the intensification factor based on the weight of each component is developed. Finally, principal component analysis fusion is employed to improve the overall colour and contrast of the output video frames. Qualitative and quantitative evaluations on the standard underwater video dataset are demonstrated to validate the improved performance of the proposed algorithm.

Underwater image enhancement via red channel maximum attenuation prior and multi-scale detail fusion.

The underwater environment poses great challenges, which have a negative impact on the capture and processing of underwater images. However, currently underwater imaging systems cannot adapt to various underwater environments to guarantee image quality. To address this problem, this paper designs an efficient underwater image enhancement approach that gradually adjusts colors, increases contrast, and enhances details. Based on the red channel maximum attenuation prior, we initially adjust the blue and green channels and correct the red channel from the blue and green channels. Subsequently, the maximum and minimum brightness blocks are estimated in multiple channels to globally stretch the image, which also includes our improved guided noise reduction filtering. Finally, in order to amplify local details without affecting the naturalness of the results, we use a pyramid fusion model to fuse local details extracted from two methods, taking into account the detail restoration effect of the optical model. The enhanced underwater image through our method has rich colors without distortion, effectively improved contrast and details. The objective and subjective evaluations indicate that our approach surpasses the state-of-the-art methods currently. Furthermore, our approach is versatile and can be applied to diverse underwater scenes, which facilitates subsequent applications.