LOCAL FEATURE EXTRACTION IN IMAGES
Anatoliy Sergiyenko, Pavlo A. Serhiienko, М. Орлова · Information, computing and intelligent systems · 2021
The methods of the local feature point extraction are analyzed. The analysis shows that the most effective detectors are based on the brightness gradient determination. They usually use the Harris angle detector, which is complex in calculations. The algorithm complexity minimization contradicts both the detector effectiveness and to the high dynamic range of the analyzed image. As a result, the high-speed methods could not recognize the feature points in the heavy luminance conditions. The modification of the high dynamic range (HDR) image compression algorithm based on the Retinex method is proposed. It contains an adaptive filter, which preserves the image edges. The filter is based on a set of feature detectors performing the Harris-Laplace transform which is much simpler than the Harris angle detector. A prototype of the HDR video camera is designed which provides sharp images. Its structure simplifies the design of the artificial intelligence engine, which is implemented in FPGA of medium or large size.