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2DPCA for Vehicle Detection from CCTV Captured Image
By: Suppatoomsin, C.; Srikaew, A.;
2011 / IEEE / 978-1-4244-9224-4
Description
This item was taken from the IEEE Conference ' 2DPCA for Vehicle Detection from CCTV Captured Image ' 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 50x20 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.
Related Topics
Road Vehicles
Engineering
Feature Extraction
Genetic Algorithms
Image Colour Analysis
Object Detection
Bilinear Interpolation
2dpca
Vehicle Detection
Cctv Captured Image
2d Principal Component Analysis
Genetic Algorithm
Feature Extraction
Gray Scale Images
Vehicle Feature Matrices
Proportional Image Area
Vehicles
Vehicle Detection
Feature Extraction
Training
Gallium
Genetic Algorithms
Principal Component Analysis
Principal Component Analysis
Closed Circuit Television
