Title :
2DPCA for Vehicle Detection from CCTV Captured Image
Author :
Suppatoomsin, Chompoo ; Srikaew, Arthit
Author_Institution :
Eng. Dept., Vongchavalitkul Univ., Nakhon Ratchasima, Thailand
Abstract :
This paper has proposed an application of 2D principal component analysis (2DPCA) and genetic algorithm (GA) for vehicle detection from CCTV captured image. The system deploys a 2DPCA algorithm for feature extraction of vehicle within gray scale images. These vehicle feature matrices of size 50×20 are trained and then classified by using genetic algorithm. This system can detect different vehicle sizes from different proportional image area. Bilinear interpolation is used to resize each proportional image area to vehicle feature matrix. The proposed system can detect various type of vehicles at the maximum accuracy of 95 percents.
Keywords :
closed circuit television; feature extraction; genetic algorithms; image colour analysis; object detection; principal component analysis; road vehicles; 2D principal component analysis; 2DPCA; CCTV captured image; bilinear interpolation; feature extraction; genetic algorithm; gray scale images; proportional image area; vehicle detection; vehicle feature matrices; Feature extraction; Gallium; Genetic algorithms; Principal component analysis; Training; Vehicle detection; Vehicles;
Conference_Titel :
Information Science and Applications (ICISA), 2011 International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-9222-0
Electronic_ISBN :
978-1-4244-9223-7
DOI :
10.1109/ICISA.2011.5772313
