Proposed Quality Assessment Method Research Articles

An improved EnlightenGAN shadow removal framework for images of cracked concrete

The concrete crack images in engineering are usually obscured by unexpected shadow and their removal is usually required which is always a challenging task due to its complexity and diversity. An improved Enlighten Generative Adversarial Networks (IEnlightenGAN) is developed in a proposed framework to improve shadow removal results. The Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) is firstly developed to improve the concrete image resolution. Residual-in-residual-dense blocks module and Atrous Spatial Pyramid Pooling module are then integrated into the IEnlightenGAN to improve its shadow removal capability. A quality assessment methodology on the shadow removal results is also proposed. The crack contour is extracted based on U-Net, and denoising is conducted based on morphological closing. Image segmentation metrics are used for the evaluation. The proposed IEnlightenGAN and the evaluation method are trained and verified using a dataset containing both normal and shadowed concrete crack images with comparison of results from the state-of-the-art models. The proposed shadow removal framework is found able to improve the quality of shadowed crack images, and the proposed quality assessment method is also found better than existing approach.

Limitations of the new ISO standard for health and wellness apps

Limitations of the new ISO standard for health and wellness apps

A Kinematic Data Based Lower Limb Motor Function Evaluation Method for Post-Stroke Rehabilitation.

Recent studies have demonstrated that home-based rehabilitation for stroke patients has excellent potential in reducing the cost and enhancing rehabilitation efficiency. Nonetheless, a timely and accurate rehabilitation assessment is required to attain efficacy and provide feedback to both clinicians and patients. In this paper, a lower limb motor function assessment approach based on limb kinematic data has been presented. The kinematic characteristics of lower limbs were quantified into specific evaluation parameters, which were calculated during a set of selected rehabilitation exercises. A body area network composed of two triaxial accelerometers was used to acquire the limb kinematic data of twenty stroke patients and six healthy subjects. While a referenced template was developed using the data from healthy subjects, an empirical score was obtained to evaluate the lower-limb motor function of stroke patients from the calculated parameters. The results have demonstrated that the scoring has a statistically significant strong correlation with the Brunnstrom stage classification, which provides a practical quantitative evaluation approach for home-based rehabilitation for lower limbs of stroke patients.Clinical Relevance- The proposed quality assessment method provides practical technical support for performing early support discharge rehabilitation.

Quality assessment for inspection images of power lines based on spatial and sharpness evaluation

Digital imaging and image-processing techniques have revolutionized the way of power line inspection in recent years. Massive images are captured and utilized for further processing to maintain the reliability, safety, and sustainability of power transmission. For power line inspection, the component region in the delivered images is required to be centered, large, and clear enough. In this paper, a component-oriented image quality assessment method is proposed to automatically predict image quality according to the demand of power line inspection. The proposed method considers two factors: spatial characteristic evaluation and sharpness evaluation. The spatial characteristic evaluation utilizes YOLOv3 to evaluate whether the component region is sufficiently centered and large, which enables the observer to quickly find the target. The sharpness evaluation employs ResNet to evaluate the clarity of component and makes the condition monitoring more accurately. For final quality assessment, a multi-stage filtering strategy is presented to aggregate these two factors and obtain high quality inspection images. The experimental results indicate that the high-quality images can be accurately identified to satisfy the requirements of power line inspection. The proposed quality assessment method enhances the efficiency for further data analysis of aerial images.

A Proposal of a Method for Ready-Mixed Concrete Quality Assessment Based on Statistical-Fuzzy Approach.

Control of technical parameters obtained by ready-mixed concrete may be carried out at different stages of the development of concrete properties and by different participants involved in the construction investment process. According to the European Standard EN 206 “Concrete–Specification, performance, production and conformity”, mandatory control of concrete conformity is conducted by the producer during production. As shown by the subject literature, statistical criteria set out in the standard, including the method for concrete quality assessment based on the concept of concrete family, continue to evoke discussions and raise doubts. This justifies seeking alternative methods for concrete quality assessment. This paper presents a novel approach to quality control and classification of concrete based on combining statistical and fuzzy theories as a means of representation of two types of uncertainty: random uncertainty and information uncertainty. In concrete production, a typical situation when fuzzy uncertainty can be taken into consideration is the conformity control of concrete compressive strength, which is conducted to confirm the declared concrete class. The proposed procedure for quality assessment of a concrete batch is based on defining the membership function for the considered concrete classes and establishing the degree of belonging to the considered concrete class. It was found that concrete classification set out by the standard includes too many concrete classes of overlapping probability density distributions, and the proposed solution was to limit the scope of compressive strength to every second class so as to ensure the efficacy of conformity assessment conducted for concrete classes and concrete families. The proposed procedures can lead to two types of decisions: non-fuzzy (crisp) or fuzzy, which point out to possible solutions and their corresponding preferences. The suggested procedure for quality assessment allows to classify a concrete batch in a fuzzy way with the degree of certainty less than or equal to 1. The results obtained confirm the possibility of employing the proposed method for quality assessment in the production process of ready-mixed concrete.

Efficient VR Video Representation and Quality Assessment

VR video is increasingly popular due to the recent advances in VR technology and hardware. The bulky size of VR video, however, impose new challenges in its storage and processing. In this paper, we focus on the research problems of VR video representation and objective quality assessment. Distinct from traditional 2D video, a VR video is displayed and represented in a form of spherical surface. For encoding purpose, a VR video frame needs to be projected to a 2D flat plane. Existing projection methods usually lead to much redundancy or significant violation in the correlation of neighbor pixels, which are not encoding friendly or are creating visible edge artifacts. To alleviate these problems, we propose in this paper our Quadrangle Affine Square Projection (QASP). QASP is a novel representation for VR video frames, which can reduce the redundant pixels over the traditional projections. In particular, all the inner pixels in QASP remain connected, i.e. the correlations between neighbors pixels are well maintained, which is a desirable feature for video encoding and edge-artifact-free viewing experience. Besides, we also investigated in predicting the optimal rotation angle for QASP frames for higher encoding efficiency. In addition to VR video representation, we also investigate in this paper accurate objective quality measurement for VR video. The traditional video quality measurements, e.g. PSNR, are not suitable to measure the quality of VR videos since they will take the redundant pixels into account. In this paper, we propose a new quality measurement for VR videos, named as Resized-PSNR (R-PSNR). With R-PSNR, only the “meaningful” pixels are considered for quality measurement while the redundant pixels are discarded. To evaluate QASP and R-PSNR, experiments are conducted based on standard VR video sequences. The experimental results show that the proposed projection method achieves noticeable improvement over traditional methods, and the proposed quality assessment method outperforms the traditional measurements in terms of consistency with subjective evaluation.

Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images

Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.

Novel read density distribution score shows possible aligner artefacts, when mapping a single chromosome

BackgroundThe use of artificial data to evaluate the performance of aligners and peak callers not only improves its accuracy and reliability, but also makes it possible to reduce the computational time. One of the natural ways to achieve such time reduction is by mapping a single chromosome.ResultsWe investigated whether a single chromosome mapping causes any artefacts in the alignments’ performances. In this paper, we compared the accuracy of the performance of seven aligners on well-controlled simulated benchmark data which was sampled from a single chromosome and also from a whole genome.We found that commonly used statistical methods are insufficient to evaluate an aligner performance, and applied a novel measure of a read density distribution similarity, which allowed to reveal artefacts in aligners’ performances.We also calculated some interesting mismatch statistics, and constructed mismatch frequency distributions along the read.ConclusionsThe generation of artificial data by mapping of reads generated from a single chromosome to a reference chromosome is justified from the point of view of reducing the benchmarking time. The proposed quality assessment method allows to identify the inherent shortcoming of aligners that are not detected by conventional statistical methods, and can affect the quality of alignment of real data.

Objective Quality Assessment and Perceptual Compression of Screen Content Images.

Screen content image (SCI) has recently emerged as an active topic due to the rapidly increasing demand in many graphically rich services such as wireless displays and virtual desktops. SCIs are often composed of pictorial regions and computer generated textual/graphical content, which exhibit different statistical properties that often lead to different viewer behaviors. Inspired by this, we propose an objective quality assessment approach for SCIs that incorporates both visual field adaptation and information content weighting into structural similarity based local quality assessment. Furthermore, we develop a perceptual screen content coding scheme based on the newly proposed quality assessment measure, targeting at further improving the SCI compression performance. Experimental results show that the proposed quality assessment method not only better predicts the perceptual quality of SCIs, but also demonstrates great potentials in the design of perceptually optimal SCI compression schemes.

Bone matrix vesicle-bound alkaline phosphatase for the assessment of peripheral blood admixture to human bone marrow aspirates

PurposePeripheral blood (PB) admixture should be minimized during numerical and functional, as well as cytokinetic analysis of bone marrow (BM) aspirates for research purposes. Therefore, purity assessment of the BM aspirate should be performed in advance. We investigated whether bone matrix vesicle (BMV)-bound bone alkaline phosphatase (ALP) could serve as a marker for the purity of BM aspirates. ResultsTotal ALP activity was significantly higher in BM serum (97 (176–124)U/L, median (range)) compared to PB serum (63 (52–73)U/L, p<0.001). Agarose gel electrophoresis showed a unique bone ALP fraction in BM, which was absent in PB. Native polyacrylamide gel electrophoresis revealed the high molecular weight of this fraction, corresponding with membrane-bound ALP from bone matrix vesicles (BMV), as evidenced by electron microscopy. A serial PB admixture experiment of bone cylinder supernatant samples, rich in BMV-bound ALP, confirmed the sensitivity of this proposed quality assessment method. Furthermore, a BMV ALP fraction of ≥15% is suggested as cut-off value for minimal BM quality. Moreover, the BM purity declines rapidly with larger aspirated BM volumes. ConclusionThe exclusive presence of BMV-bound ALP in BM could serve as a novel marker to assess purity of BM aspirates.

Quality Analysis of Indian Basmati Rice Grains using Top-Hat Transformation

is one of the most important cereal grains. Rice is a good source of complex carbohydrates and is rich in several other essential nutrients. The paper presents a solution for quality analysis of Indian Basmati rice grains using Top-hat Transformation. In this paper the problem of Non-uniform Illumination for quality assessment is defined which show their effects in the process of extracting objects from the background and cause segmentation errors. The proposed method for quality assessment of Indian Basmati rice grains using Top-hat Transformation which achieves high degree of accuracy in correcting the effects of the Non-uniform Illumination than Computer Vision Inspection. The proposed method based on Morphological features is developed for counting the number of Indian Basmati rice grains with Normal grains, Long grains and Small grains. Keywords-hat Transformation, Quality, Morphological operations, Basmati rice grains, Parameters

New Finger-vein Recognition Method Based on Image Quality Assessment

The performance of finger-vein recognition methods is limited by camera optical defocusing, the light-scattering effect of skin, and individual variations in the skin depth, density, and thickness of vascular patterns. Consequently, all of these factors may affect the image quality, but few studies have conducted quality assessments of finger-vein images. Therefore, we developed a new finger-vein recognition method based on image quality assessment. This research is novel compared with previous methods in four respects. First, the vertical cross-sectional profiles are extracted to detect the approximate positions of vein regions in a given finger-vein image. Second, the accurate positions of the vein regions are detected by checking the depth of the vein’s profile using various depth thresholds. Third, the quality of the finger-vein image is measured by using the number of detected vein points in relation to the depth thresholds, which allows individual variations of vein density to be considered for quality assessment. Fourth, by assessing the quality of input finger-vein images, inferior-quality images are not used for recognition, thereby enhancing the accuracy of finger-vein recognition. Experiments confirmed that the performance of finger-vein recognition systems that incorporated the proposed quality assessment method was superior to that of previous methods.

Multiple distortion pooling image quality assessment

This paper presents a quality assessment method which pools some basic image quality assessment parameters and empirically combines them in such a manner to evaluate across different distortion types. The proposed quality metric (Q) is formulated by modelling an image distortion as a combined effect of structural distortion, contrast distortion and edge distortion, which may occur on account of deteriorations due to noise contamination, contrast manipulations, blurring, rotation or compression. The values of the correlation coefficient prove that this metric provides an accurate estimation for the above mentioned distortions in comparison to mean squared error (MSE) and structural similarity measure (SSIM). Results of subjective evaluation also validate the efficiency of the proposed quality assessment method and its ability to quantify the effect of different distortions under a single quality metric.

주파수 도메인 정보를 이용한 영상의 Sharpness 평가 방법

본 논문에서는 영상의 선명도를 영상의 주파수 도메인 정보를 이용하여 측정하는 새로운 무기준법 화질 평가 방법을 제안한다. 기존에, 영상에 대한 선명도는 일반적으로 영상의 픽셀 값을 이용하여 측정되었다. 제안된 방법은 기존 방법과 달리 영상에 대한 선명도를 주파수 도메인 정보를 이용하여 측정하였다. 주파수 도메인에서 선명도를 평가하기 위하여 주어진 영상은 가우시안 저주파 필터를 사용하여 열화 되고, 열화 영상과 주어진 영상의 주파수 영역 계수를 사용하여 새로운 선명도 평가 함수를 정의하였다. 제안된 방법의 성능 검증은 TID2008 화질 평가 데이터베이스를 사용하여 이루어졌다. 기존 무기준법 영상 선명도 평가 방법과 비교하였을 때, 제안된 선명도 평가 방법은 주관적 화질 점수와 보다 높은 상관도를 보였다. In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.

Perceived Coding Distortion Assessment for Streaming Video

For applications involving video streaming, full decoding is usually not acceptable for quality assessment. To address the inherent challenges, an efficient method for coding distortion assessment is proposed in this paper. Building on empirical analysis, the proposed method employs a linear model to assess the coding distortion using the quantization scale. Furthermore, the characteristics of the human visual system are exploited by taking into account the spatial and temporal masking. To estimate the required spatial and temporal complexities in absence of sufficient information, a rate-distortion model is theoretically derived to formulate their relationship with the coding bit-rate. Extensive experimental results have demonstrated the effectiveness of the proposed method for quality assessment with respect to perceived coding distortion.

Reduced-Reference Quality Assessment for JPEG-2000 Compressed Image

Image quality assessment method is a methodology that measures the difference of quality between the reference image and its distorted one. In this paper, we propose a novel reduced-reference (RR) quality assessment method for JPEG-2000 compressed images, which exploits the statistical characteristics of context information extracted through partial entropy decoding or decoding. These statistical features obtained in the process of JPEG-2000 encoding are transmitted to the receiver as side information and used to estimate the quality of images transmitted over various noisy channels at the decompression side. In the framework of JPEG-2000, the context of a current coefficient is determined depending on the pattern of the significance and/or the sign of its neighbors in three bit-plane coding passes and four coding modes. As the context information represents the local property of images, it can efficiently describe textured pattern and edge orientation. The quality of transmitted images is measured by the difference of entropy of context information between received and original images. Moreover, the proposed quality assessment method can directly process the images in the JPEG-2000 compressed domain without full decompression. Therefore, our proposed can accelerate the work of assessing image quality. Through simulations, we demonstrate that our method achieves fairly good performance in terms of the quality measurement accuracy as well as the computational complexity.