Parking cell detection of multiple video features with PCA-and- Bayes-based classifier
Parking cell detection is one of the key technologies in parking lot monitoring and management system, this article proposes the parking cell detection algorithm of multiple video features with PCA-and-Bayes-based classifier, in view of complex background and the different environment illumination condition in the parking lot. Firstly, this article has fully used the geometrical and statistical features of parking cell information, and extracted the features parameter of parking cell. Then the classifier is designed with PCA-and- Bayes-based discrimination. Finally, many images, which are regarded as the parking cell detection image in the different weather and environment conditions continuously 14 days, are tested by the proposed algorithm, and made comparisons with the results between the proposed algorithm and other algorithms. The experimental result indicated that the algorithm proposed in this article is superior to other algorithms in aspects of operation time, recognition accuracy, and the robustness. Its detection rate reaches as high as 98.99％.
parking cell detection multi-features parameter principal components (PCA) Bayes discrimination
Hongli Deng Dalin Jiang Yanfeng Wei
School of Electronic Information & Control Engineering Beijing University of Technology Beijing, Peoples Republic of China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
655-659
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）