Beschreibung
Edge detection plays a vital role in the areas of feature detection and feature extraction. Conventionally, manual operations were performed to set the window size for extracting edge features. Noise rejection and edge localization are the two contradicting offset in selection of window size. To overcome this drawback genetic programming is proposed to search pixels automatically to construct new edge features for detecting edges in real images. The proposed method avoids the problem of blurring (large window) and noise effect (small window) by selecting the window size. Genetic programming is used for feature detection and feature extraction to produce rich information and improves classification accuracy. The main aim of feature extraction is to reduce the unwanted data and transform the data bit into a reduced set of features. MATLAB and Verilog is used for simulation and implemented on Xilinx virtex-5 FPGA.
Autorenporträt
Mrs. G. Mahalakshmi Malini, Assistant Professor & Dr. R. Sudarmani, Associate Professor currently working in the Department of Electronics and Communication Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women. I done this project in the field of MATLAB and Xilinx. Hope it will be helpful.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
