Visual and Automatic Evaluation of Vocal Fold Mucosal Waves Through Sharpness of Lateral Peaks in High-Speed Videokymographic Images.

INTRODUCTION: The sharpness of lateral peaks is a visually helpful clinical feature in high-speed videokymographic (VKG) images indicating vertical phase differences and mucosal waves on the vibrating vocal folds and giving insights into the health and pliability of vocal fold mucosa. This study aims at investigating parameters that can be helpful in objectively quantifying the lateral peak sharpness from the VKG images. METHOD: Forty-five clinical VKG images with different degrees of sharpness of lateral peaks were independently evaluated visually by three raters. The ratings were compared to parameters obtained by automatic image analysis of the vocal fold contours: Open Time Percentage Quotients (OTQ) and Plateau Quotients (PQ). The OTQ parameters were derived as fractions of the period during which the vocal fold displacement exceeds a predetermined percentage of the vibratory amplitude. The PQ parameters were derived similarly but as a fraction of the open phase instead of a period. RESULTS: The best correspondence between the visual ratings and the automatically derived quotients were found for the OTQ and PQ parameters derived at 95% and 80% of the amplitude, named OTQ95, PQ95, OTQ80 and PQ80. Their Spearman's rank correlation coefficients were in the range of 0.73 to 0.77 (P < 0.001) indicating strong relationships with the visual ratings. The strengths of these correlations were similar to those found from inter-rater comparisons of visual evaluations of peak sharpness. CONCLUSION: The Open time percentage and Plateau quotients at 95% and 80% of the amplitude stood out as the possible candidates for capturing the sharpness of the lateral peaks with their reliability comparable to that of visual ratings.

Detection of copy-move image modification using JPEG compression model.

The so-called copy-move forgery, based on copying an object and pasting in another location of the same image, is a common way to manipulate image content. In this paper, we address the problem of copy-move forgery detection in JPEG images. The main problem with JPEG compression is that the same pixels, after moving to a different position and storing in the JPEG format, have different values. The majority of existing algorithms is based on matching pairs of similar patches, which generates many false matches. In many cases they cannot be eliminated by postprocessing, causing the failure of detection. To overcome this problem, we derive a JPEG-based constraint that any pair of patches must satisfy to be considered a valid candidate and propose an efficient algorithm to verify the constraint. The constraint can be integrated into most existing methods. Experiments show significant improvement of detection, especially for difficult cases, such as small objects, objects covered by textureless areas and repeated patterns.

Automatic blood detection in capsule endoscopy video.

We propose two automatic methods for detecting bleeding in wireless capsule endoscopy videos of the small intestine. The first one uses solely the color information, whereas the second one incorporates the assumptions about the blood spot shape and size. The original idea is namely the definition of a new color space that provides good separability of blood pixels and intestinal wall. Both methods can be applied either individually or their results can be fused together for the final decision. We evaluate their individual performance and various fusion rules on real data, manually annotated by an endoscopist.

PIZZARO: Forensic analysis and restoration of image and video data.

This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.