Quality Assessment Measures Research Articles

Spoof detection on face and palmprint biometrics

Spoofing attacks made by non-real images are a major concern to biometric systems. This paper presents a novel solution for distinguishing between live and forged identities using the fusion of texture-based methods and image quality assessment measures. In our approach, we used LBP and HOG texture descriptors to extract texture information of an image. Additionally, feature space of seven full-reference complementary image quality measures is considered including peak signal-to-noise ratio, structural similarity, mean-squared error, normalized cross-correlation, maximum difference, normalized absolute error and average difference. We built a palmprint spoof database made by printed palmprint photograph of PolyU palmprint database using camera. Experimental results on three public-domain face spoof databases (Idiap Print-Attack, Replay-Attack and MSU MFSD) and palmprint spoof database show that the proposed solution is effective in face and palmprint spoof detection.

The ESRD Quality Incentive Program-Can We Bridge the Chasm?

The ESRD Quality Incentive Program (QIP) is the first mandatory federal pay for performance program launched on January 1, 2012. The QIP is tied to the ESRD prospective payment system and mandated by the Medicare Improvements for Patients and Providers Act of 2008, which directed the Centers for Medicare and Medicaid Services to expand the payment bundle for renal dialysis services and legislated that payment be tied to quality measures. The QIP links 2% of the payment that a dialysis facility receives for Medicare patients on dialysis to the facility's performance on quality of care measures. Quality measures are evaluated annually for inclusion on the basis of importance, validity, and performance gap. Other quality assessment programs overlap with the QIP; all have substantial effects on provision of care as clinicians, patients, regulators, and dialysis organizations scramble to keep up with the frequent release of wide-ranging regulations. In this review, we provide an overview of quality assessment and quality measures, focusing on the ESRD QIP, its effect on care, and its potential future directions. We conclude that a patient-centered, individualized, and parsimonious approach to quality assessment needs to be maintained to allow the nephrology community to further bridge the quality chasm in dialysis care.

Image Quality Assessment Using Edge Correlation

Abstract In literature, oriented filters are used for low-level vision tasks. In this paper, we propose use of steerable Gaussian filter in image quality assessment. Human visual system is more sensitive to multidirectional edges present in natural images. The most degradation in image quality is caused due to its edges. In this work, an edge based metric termed as steerable Gaussian filtering (SGF) quality index is proposed as objective measure for image quality assessment. The performance of the proposed technique is evaluated over multiple databases. The experimental result shows that proposed method is more reliable and outperform the conventional image quality assessment method.

Test of the HAPD light sensor for the Belle II Aerogel RICH

The Aerogel Ring-Imaging Cherenkov detector (ARICH) is being installed in the endcap region of Belle II spectrometer to identify particles from B meson decays by detecting the Cherenkov ring image from aerogel radiators. To detect single photons, high-sensitive photon detector which has wide effective area (∼70mm × 70mm), a Hybrid Avalanche Photo Detector (HAPD), has been developed in a collaboration with Hamamatsu K.K. The HAPD consists of hybrid structure of a vacuum tube and an avalanche photodiode (APD). It can be operated in 1.5T magnetic field of the spectrometer and withstands the radiation levels expected in the Belle II experiment. There are two steps of electric pulse amplification: acceleration of photo-electron in electric field in the vacuum tube part and electron avalanche in the APD part resulting in total gain of order 105. For the ARICH, we use 420 HAPDs in total. Before installing them, we performed quality assessment studies such as measurements of dark current, noise level, signal-to-noise ratio and two-dimensional scan with laser illumination. We also measured quantum efficiency of the photocathode. During the HAPD performance tests in the magnetic field, we observed very large signal pulses which cause long dead time of the readout electronics in some of the HAPDs. We have carried out a number of studies to understand this phenomenon, and have found a way to mitigate it and suppress the degradation of the ARICH performance. In this report, we will show a summary of the HAPD performance and quality assessment measurements including validation in the magnetic field for all of the HAPDs manufactured for the ARICH in the Belle II.

An entropy based approach for SSIM speed up

This paper focuses on an entropy based formalism to speed up the evaluation of the Structural SIMilarity (SSIM) index in images affected by a global distortion. Looking at images as information sources, a visual distortion typical set can be defined for SSIM. This typical set consists of just a subset of information belonging to the original image and the corresponding one in the distorted version. As side effect, some general theoretical criteria for the computation of any full reference quality assessment measure can be given in order to maximize its computational efficiency. Experimental results on various test images show that the proposed approach allows to estimate SSIM with a considerable speed up (about 200 times) and a small relative error (often lower than 5%).

Towards automated quality assessment measure for EEG signals

EEG signals provide the means to understand how the brain works and they can be used within a wide range of applications; especially BCI applications. The main issue that affects the performance of such applications is the quality of the recorded EEG signal. Noise produced during the recording of the EEG signal impacts directly on the quality of the acquired neural signal. BCI applications performance is susceptible to the quality of the EEG signal. Most BCI research focuses on the effectiveness of the selected features and classifiers. However, the quality of the input EEG signals is determined manually. This paper proposes an automated signal quality assessment method for the EEG signals. The proposed method generates an automated quality measure for each EEG frequency window based on the EEG signal bands characteristics as well as their noise levels. Six scores were developed in this research and the quality of the EEG signal is postulated based on these scores. This EEG quality assessment measure will give researchers an early indication of the quality of the signal. This research will help in testing new BCI algorithms so that the testing could be made on only high quality signals. It will also help BCI applications to react to high quality signals and ignore lower quality ones without the need for manual interference. EEG data acquisition experiments were conducted with different levels of noise and the results show the consistency of our algorithms in estimating the accurate signal quality measure.

A Regression-Based Family of Measures for Full-Reference Image Quality Assessment

Abstract The advances in the development of imaging devices resulted in the need of an automatic quality evaluation of displayed visual content in a way that is consistent with human visual perception. In this paper, an approach to full-reference image quality assessment (IQA) is proposed, in which several IQA measures, representing different approaches to modelling human visual perception, are efficiently combined in order to produce objective quality evaluation of examined images, which is highly correlated with evaluation provided by human subjects. In the paper, an optimisation problem of selection of several IQA measures for creating a regression-based IQA hybrid measure, or a multimeasure, is defined and solved using a genetic algorithm. Experimental evaluation on four largest IQA benchmarks reveals that the multimeasures obtained using the proposed approach outperform state-of-the-art full-reference IQA techniques, including other recently developed fusion approaches.

Application of surrogate measures of ecological quality assessment: The introduction of the Indicator of Ecological Landscape Quality (IELQ)

Despite the fact that many ecological landscape indicators have been applied so far, it is challenging to develop an indicator(s) which is easy and cheap to assess while at the same time reflecting the complexity of an ecosystem. The author aimed at the development of such an indicator: the Indicator of Ecological Landscape Quality (IELQ) which ranged from 0 to 2. This is based on the use of surrogate measures of assessing ecological quality (EQ) and a GIS approach. The employed measures include: landscape diversity, the degree of ecological significance of land cover forms, and the character of linear landscape structures. To verify the validity of the adopted measures, the indicator was calculated for areas under different conservation statuses and adjoining non-protected areas located in eastern Poland, 20 sites in total. The results showed that differences in mean IELQ values between areas under different protection regimes are significant (Tukey: p<0.01). The highest mean values were obtained for nature reserves (0.86), and the lowest for non-protected areas (0.27). Explanatory factors for EQ included the proportion of natural and anthropogenic land cover forms, and the number of land cover forms. Surprisingly, the correlation between the latter factor and IELQ is negative (−0.704), indicating that the lower the landscape diversity, the higher the ecological values. From the protected area management point of view, the developed indicator proved its usefulness in terms of an assessment of ecological values and indicated changes in values over time.

The effect of prosody awareness training on the performance of consecutive interpretation by Farsi-English interpreter trainees: an experimental study

This study investigates the effect of prosody awareness training on the performance of Farsi-English interpreter trainees. Two groups of student interpreters were formed. All were native speakers of Farsi who studied English translation and interpreting at the BA level at the State University of Arak, Iran. Participants were assigned to groups at random, but with equal division between genders (8 female and 8 male students in each group). At the beginning of the program, all the participants took a pretest of general English proficiency. No significant differences in English language skills (TOEFL scores) could be established between the groups. Three expert raters assessed quality measures of interpreting performance in both a pretest and a post-test. All rating scales that pertain to prosodic aspects in the trainees’ interpreting performance, proved susceptible to the explicit teaching of prosody. The results of the study showed that explicit teaching of prosody statistically did have a positive effect on the overall interpreting performance by Farsi-English interpreter trainees. The pedagogical implications of the present study would pertain to interpreting programs all over the world. Course developers should take these results into considerations and include contrastive prosody in the textbooks for interpreting programs.

Operative wound classification: an inaccurate measure of pediatric surgical morbidity

BackgroundWound classification has catapulted to the forefront of surgical literature and quality care discussions. However, it has not been validated in laparoscopy or children. We analyzed pediatric infection rates based on wound classification and reviewed the most common noninfectious complications which could be a more appropriate measure for quality assessment. MethodsWe performed a retrospective review of 800 patients from 2011 to 2014 undergoing common procedures at a tertiary pediatric hospital. Demographics, procedure, wound classification and complications were analyzed using descriptive statistics. ResultsInfection rates were in the expected low range for clean procedures. However, 5% of pyloromyotomy patients required readmission and 10% of circumcision patients developed penile adhesions; 2% required reoperation. Ostomy reversal, a clean contaminated case, had 17% wound infections, whereas acute appendicitis, a contaminated case had only a 4% infection rate. Laparoscopic cholecystectomy (clean-contaminated or contaminated depending on inflammation) had 2% postoperative infections. Perforated appendicitis, a dirty procedure had an 18% infection rate, below the expected >27% for dirty cases in adults. ConclusionsCurrent wound classifications do not accurately approximate the risk of surgical site infections in children, particularly for laparoscopic procedures. It would be more appropriate to grade hospitals based on disease and procedure specific complications.

Critical Binocular Asymmetry Measure for the Perceptual Quality Assessment of Synthesized Stereo 3D Images in View Synthesis

In human vision, excessive binocular asymmetry between the left- and right-eye images can be very problematic to perceive single binocular vision (causing visual discomfort) in the viewing of stereoscopic images. In this paper, we propose a critical binocular asymmetry (CBA) measure for objectively assessing the perceptual quality of the synthesized stereo 3D images generated through a depth-image-based rendering (DIBR) process. The proposed method detects critical regions that are likely to induce excessive binocular asymmetry. In particular, this paper considers view extrapolation since it introduces much more artifacts due to the lack of data. We measure structural similarity on the critical regions between the left and right images to quantify the perceptual effects of binocular asymmetry. The effectiveness of the proposed quality measure has been successfully evaluated by subjective assessment experiments using various types of synthesized stereoscopic images generated by four different DIBR-based view synthesis algorithms. We demonstrate the validity of the proposed quality measure by the comparison of subjective ratings and existing objective methods. Experimental results show that the combined use of the proposed binocular asymmetry measure and existing quality measures substantially improves the performance of the quality measures by explicitly considering the perceptual effects of CBA.

PAN-SHARPENING APPROACHES BASED ON UNMIXING OF MULTISPECTRAL REMOTE SENSING IMAGERY

Abstract. Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods ‘better’ satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald’s protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property ‘better’ should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

PAN-SHARPENING APPROACHES BASED ON UNMIXING OF MULTISPECTRAL REMOTE SENSING IMAGERY

Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods ‘better’ satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald’s protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property ‘better’ should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

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.

Skeletal survey quality in non-accidental injury – A single site evaluation of the effects of imaging checklists

AimsEvidence suggests ongoing practice variability in the quality of skeletal survey examinations for non-accidental injury. The purpose of the study was to investigate the effects on examination quality following the implementation of imaging checklists. MethodA retrospective evaluation of skeletal survey examinations was carried out on studies performed between January 2007 and November 2014 at a large District General Hospital Trust. Longitudinal assessment was undertaken over three periods, before and following the introduction of two versions of imaging checklists, following modifications. Examinations were assessed and scored using three measures for completeness and quality employing a modified established scoring system against a professional body national standards document. ResultsA total of 121 examinations met the inclusion criteria, all quality assessment measures showed improvements between each period. Examination completeness increased from median of 13 projections, to 20 throughout the three periods. Mann Whitney u Tests showed significant differences between each period. The mean combined anatomy score reduced from 3.11 to 1.10 throughout the three periods. Independent t Tests and Mann Whitney u Tests showed a significant decrease throughout the study period. Total percentage examination quality increased from median 44–83% throughout the three periods. Independent t Tests also showed significant differences between each period. ConclusionThe use of imaging checklists to improve quality and to support the optimal acquisition of the non-accidental injury skeletal survey shows encouraging results. However, further work is needed to optimise content and the use of checklists in practice.

Non-Gaussian and persistence measures for control loop quality assessment.

This paper presents review and comparison of alternative methodologies for control performance assessment. The approach uses nonlinear time series analysis, such as non-Gaussian statistics, fractal, crossover analysis, or entropy-based approaches. There is a presented practical rationale for the analysis. Evaluation is based on the real data gathered from industrial systems. Non-Gaussian analysis starts with statistical methods using different probabilistic distribution functions. As another potential measure, the Hurst exponent is calculated using different approaches. Finally, R/S plot analysis together with crossover point phenomenon discussion is presented. The paper ends with conclusions and presentation of open issues attractive for further development.

Study of No-Reference Video Quality Metrics for HEVC Compression

The paper proposes a No-Reference (NR) quality assessment measurement originally developed for H.264, used for High Efficiency Video Coding (HEVC). In particular, authors present an investigation of NR metrics to objectively estimate the perceptual quality of a set of processed video sequences. The authors take into account typical distortions introduced by the block-based coding approaches like HEVC codec. The underlying processing used for the quality assessment considers the blockiness caused by the boundaries of each coded block and the blurring as a lack of spatial details. The correlation between the NR quality metrics and the well-known and most widely used objective metric, the Video Quality Model (VQM), is performed to validate the quality prediction accuracy based on the provided scores. The Pearson correlation coefficients obtained stand for promising results for different types of videos.

Measures Assessing the Quality of Case Conceptualization: A Systematic Review

The quality of case conceptualization differs across clinicians. It is unclear which case conceptualization quality assessment measure researchers, clinicians, and trainers might use for their specific purpose. We evaluated measures that purport to assess the quality of case conceptualizations. We searched EMBASE, PubMed, Medline, and PsycINFO databases with the terms case formulation* OR case conceptuali*ation*. Further specific terms were then used to narrow the search. Of all the articles reviewed, 8 measures of case conceptualization met inclusion criteria. There is no single measure that has been validated across a range of different settings. However, the Case Conceptualisation Coding Rating Scale, Case Formulation Content Coding Method, and Case Formulation Quality Checklist have been most robustly tested. Further research is required to test the psychometric properties of measures so that robust quality measures can be used across different settings/client groups.

A Quality Framework for Statistics based on Administrative Data Sources using the Example of the Austrian Census 2011

Along with the implementation of a register-based census we develop a methodological framework to assess administrative data sources for statistical use. Key aspects for the quality of these data are identified in the context of hyperdimensions and embedded into a process flow. Based on this approach we develop a structural quality framework and suggest a concept for quality assessment and several quality measures.

Healthcare Accreditation in Kazakhstan: Methods and Impact

In today’s health care arena, a number of issues are being raised that have received more attention either from the health care consumers or the media. Whether as a provider, a consumer or a purchaser, each was looking for ways to satisfy the other through measuring and reporting on care outcomes. All of these activities were done in the effort to measure performance. WHO organized and facilitated a number of activities related to quality assessment, performance improvement and outcome measurement. A large number of countries and institutions participated in these activities and initiatives. And at the end, all agreed that there had to be an organized mechanism to account for quality, continuous measurement and improved performance in health care organizations. In order to do this a mechanism for certification, licensure or accreditation should be put in place. In this article we will discuss the importance and the components of quality in health care and accreditation. A detailed exploration of accreditation will take the majority of discussion of this article. The process and the methodology of accreditation will be discussed and a system for its implementation is presented as a case study of Republic of Kazakhstan.