By Fábio J. Ayres, Rangaraj M. Rangayyan, J.E. Leo Desautels
The presence of orientated gains in pictures usually conveys very important information regarding the scene or the gadgets contained; the research of orientated styles is a crucial activity within the common framework of photo realizing. As in lots of different purposes of computing device imaginative and prescient, the final framework for the knowledge of orientated positive factors in pictures should be divided into low- and high-level research. within the context of the examine of orientated beneficial properties, low-level research contains the detection of orientated beneficial properties in pictures; a degree of the neighborhood significance and orientation of orientated positive factors over the complete quarter of research within the photo is termed the orientation box. High-level research pertains to the invention of styles within the orientation box, often by means of associating the constitution perceived within the orientation box with a geometric version. This e-book provides an research of numerous very important equipment for the detection of orientated positive factors in photos, and a dialogue of the part portrait technique for high-level research of orientation fields. in an effort to illustrate the thoughts constructed in the course of the ebook, an software is gifted of the section portrait technique to computer-aided detection of architectural distortion in mammograms. desk of Contents: Detection of orientated gains in pictures / research of orientated styles utilizing section pics / Optimization thoughts / Detection of web sites of Architectural Distortion in Mammograms
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Extra info for Analysis of Oriented Texture with Applications to the Detection of Architectural (Synthesis Lectures on Biomedical Engineering)
Reproduced with permission from F. J. Ayres and R. M. Rangayyan. “Design and performance analysis of oriented feature detectors”. Journal of Electronic Imaging, 16(2):12 pages, April 2007. article number 023007. 6. 12. The orientation field was obtained using a bank of 180 Gabor filters. Line segments are drawn every 10 pixels, indicating the orientation field angle. 1. Reproduced with permission from F. J. Ayres and R. M. Rangayyan. “Design and performance analysis of oriented feature detectors”.
Therefore, the ranking of the oriented feature detectors according to the combined robustness measure is consistent with the preceding discussion. The superior performance of the real Gabor, the line operator, and the steerable filters is due to the fact that the test pattern used to study the oriented feature detectors consists of line segments of positive contrast; therefore, the filters have an intrinsic advantage in the detection of the lines in the test pattern. The real Gabor, the line operator, and the steerable filters are recommended when all oriented features to be detected in an image are of positive contrast.
Nevertheless, the analysis of the optimal scale range is relevant: given a range of characteristic widths of several oriented features to be detected in an image, the analysis of the optimal scale range as above permits the appropriate selection of the scale parameter values, in the multiscale operation of each oriented feature detector. The set of scale parameter values must be chosen in such a manner that the union of the optimal scale ranges, associated with each scale chosen, covers the given range of the characteristic widths of the oriented features of interest.
Analysis of Oriented Texture with Applications to the Detection of Architectural (Synthesis Lectures on Biomedical Engineering) by Fábio J. Ayres, Rangaraj M. Rangayyan, J.E. Leo Desautels