By Andrew Creese, David Parker
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M. Rangayyan. “Design and performance analysis of oriented feature detectors”. Journal of Electronic Imaging, 16(2):12 pages, April 2007. article number 023007. 4. DISCUSSION 23 by the steerable filter, the quadrature steerable filter, the real Gabor filter, and the complex Gabor filter. 8a. 20 GHz Pentium 4 processor, 2 MB of cache, and 2 GB of RAM). 75 DISCUSSION The aim of the analysis described in this chapter was to develop design criteria and conduct performance analysis of five oriented feature detectors, in terms of their ability in the detection of oriented features and accuracy in the determination of the angle of the oriented features of interest.
Likewise, the presence of patterns that are similar to saddle or spiral patterns will cause agglomerations of votes in the respective phase portrait maps. 2, three synthetic test images exhibiting oriented texture were created. Each image is associated with a specific type of phase portrait. The images were created as follows: 1. 6. Each vector was subsequently normalized to unit length. 2. A blank image of size 512 × 512 pixels was created, and subsequently filled with randomly placed salt noise , that is, white pixels.
66. This value represents the center of the line width range in the multiscale test image. 1. 83. 83, computed above. 20 1. 10: Cumulative angular error for each oriented feature detector: steerable filter (dotted line); quadrature steerable filter (dash-dot line); real Gabor filter (dashed line); complex Gabor filter (solid line); line operator (bold solid line). The curves associated with the real and complex Gabor filters overlap significantly. Reproduced with permission from F. J. Ayres and R.
Cost Analysis in Primary Health Care: A Training Manual for Programme Managers by Andrew Creese, David Parker