Statistical analysis of image quality measures for face liveness detection

Face recognition is essential for a wide range of technologies that requires person identification. Due to the presence of spoof face attacks, an additional layer of security is needed to protect the system, which can be provided by liveness detection. In this paper we develop a technique for discriminating live from fake images. Our approach is based upon the hypothesis that spoofing scheme leave statistical indication or structure in images which can be utilized for detection by assistance of image quality features. To achieve this, image quality measures (IQMs) statistical evaluation has been implemented using the analysis of variance (ANOVA) technique. A feature set of measures with highest discrimination power to distinguish between real and fake images was obtained. This ensures the simplicity of detection system and improves its computational efficiency

Spectral imaging of human portraits and image quality

This dissertation addresses the problem of capturing spectral images for human portraits and evaluating image quality of spectral images. A new spectral imaging approach is proposed in this dissertation for spectral images of human portraits. Thorough statistical analysis is performed for spectral reflectances from various races and different face parts. A spectral imaging system has been designed and calibrated for human portraits. The calibrated imaging system has the ability to represent not only the facial skin but also the spectra of lips, eyes and hair from various races as well. The generated spectral images can be applied to color-imaging system design and analysis. To evaluate the image quality of spectral imaging systems, a visual psychophysical image quality experiment has been performed in this dissertation. The spectral images were simulated based on real spectral imaging system. Meaningful image quality results have been obtained for spectral images generated from different spectral imaging systems. To bridge the gap between the physical measures and subjective visual perceptions of image quality, four image distortion factors were defined. Image quality metrics were obtained and evaluated based statistical analysis and multiple analysis. The image quality metrics have high correlation with subjective assessment for image quality. The image quality contribution of the distortion factors were evaluated. As an extension of the work other researchers in MCSL have initiated, this dissertation research will, working with other researchers in MCSL, put effort to build a publicly accessible database of spectral images, Lippmann2000

Reducing effective dose to a paediatric phantom by using different combinations of kVp, mAs and additional filtration whilst maintaining image quality

Purpose: To determine whether using different combinations of kVp and mAs with additional filtration can reduce the effective dose to a paediatric phantom whilst maintaining diagnostic image quality. Methods: 27 images of a paediatric AP pelvis phantom were acquired with different kVp, mAs and additional copper filtration. Images were displayed on quality controlled monitors with dimmed lighting. Ten diagnostic radiographers (5 students and 5 experienced radiographers) had eye tests to assess visual acuity before rating the images. Each image was rated for visual image quality against a reference image using 2 alternative forced choice software using a 5-point Likert scale. Physical measures (SNR and CNR) were also taken to assess image quality. Results: Of the 27 images rated, 13 of them were of acceptable image quality and had a dose lower than the image with standard acquisition parameters. Two were produced without filtration, 6 with 0.1mm and 5 with 0.2mm copper filtration. Statistical analysis found that the inter-rater and intra-rater reliability was high. Discussion: It is possible to obtain an image of acceptable image quality with a dose that is lower than published guidelines. There are some areas of the study that could be improved. These include using a wider range of kVp and mAs to give an exact set of parameters to use. Conclusion: Additional filtration has been identified as amajor tool for reducing effective dose whilst maintaining acceptable image quality in a 5 year old phantom

Psychosocial factors and quality of life in adults with cystic fibrosis

The life expectancy of Cystic Fibrosis (CF) patients continues to increase, and it is therefore important to understand more about the psychosocial aspects of CF in adulthood. The present study aims to compare a group of 30 adult CF patients with a healthy control group on a multidimensional quality of life measure (WHOQOL) and other measures assessing self-esteem, anxiety, depression, social support and body image. A clinical measure of severity was also included in the CF group as were objective measures of physical functioning. The experimental group were outpatients attending the CF centre, Edinburgh. Their mean age was 29 (range=18 - 49 years). Healthy controls were a community sample matched for age, sex and deprivation category. Adjustment to illness was also assessed in the CF group and additional qualitative data relating to CF specific quality of life was obtained during semistructured interviews with 19 of the CF subjects. Statistical analysis was conducted to test the prediction that there would be no significant between groups differences on psychological measures (anxiety, depression and self-esteem). Differences were predicted in certain aspects of quality of life such as mobility and ability to work. Social support networks and body image concerns were also predicted to vary between the groups. A thematic analysis of interview data was also conducted to explore specific issues of adjustment and quality of life within the CF group

Experimental article – Reducing effective dose to a paediatric phantom by using different combinations of kVp, mAs and additional filtration whilst maintaining image quality

Purpose: To determine whether using different combinations of kVp and mAs with additional filtration can reduce the effective dose to a paediatric phantom whilst maintaining diagnostic image quality. Methods: 27 images of a paediatric AP pelvis phantom were acquired with different kVp, mAs and additional copper filtration. Images were displayed on quality controlled monitors with dimmed lighting. Ten diagnostic radiographers (5 students and 5 experienced radiographers) had eye tests to assess visual acuity before rating the images. Each image was rated for visual image quality against a reference image using 2 alternative forced choice software using a 5-point Likert scale. Physical measures (SNR and CNR) were also taken to assess image quality. Results: Of the 27 images rated, 13 of them were of acceptable image quality and had a dose lower than the image with standard acquisition parameters. Two were produced without filtration, 6 with 0.1mm and 5 with 0.2mm copper filtration. Statistical analysis found that the inter-rater and intra-rater reliability was high. Discussion: It is possible to obtain an image of acceptable image quality with a dose that is lower than published guidelines. There are some areas of the study that could be improved. These include using a wider range of kVp and mAs to give an exact set of parameters to use. Conclusion: Additional filtration has been identified as amajor tool for reducing effective dose whilst maintaining acceptable image quality in a 5 year old phantom

Quantitative Statistical Methods for Image Quality Assessment

Quantitative measures of image quality and reliability are critical for both qualitative interpretation and quantitative analysis of medical images. While, in theory, it is possible to analyze reconstructed images by means of Monte Carlo simulations using a large number of noise realizations, the associated computational burden makes this approach impractical. Additionally, this approach is less meaningful in clinical scenarios, where multiple noise realizations are generally unavailable. The practical alternative is to compute closed-form analytical expressions for image quality measures. The objective of this paper is to review statistical analysis techniques that enable us to compute two key metrics: resolution (determined from the local impulse response) and covariance. The underlying methods include fixed-point approaches, which compute these metrics at a fixed point (the unique and stable solution) independent of the iterative algorithm employed, and iteration-based approaches, which yield results that are dependent on the algorithm, initialization, and number of iterations. We also explore extensions of some of these methods to a range of special contexts, including dynamic and motion-compensated image reconstruction. While most of the discussed techniques were developed for emission tomography, the general methods are extensible to other imaging modalities as well. In addition to enabling image characterization, these analysis techniques allow us to control and enhance imaging system performance. We review practical applications where performance improvement is achieved by applying these ideas to the contexts of both hardware (optimizing scanner design) and image reconstruction (designing regularization functions that produce uniform resolution or maximize task-specific figures of merit)