Abstract: Log Gabor Filter Based Feature Detection in Image Verification Application
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064

Downloads: 106

M.Tech / M.E / PhD Thesis | Electronics & Communication Engineering | India | Volume 3 Issue 12, December 2014

Log Gabor Filter Based Feature Detection in Image Verification Application

P. Pradeep Kumar, I. Krishna Rao

In recent years due to low-cost, flexibility, and potential toward collision avoidance the Vehicle and Non Vehicle identification based on image processing bring more attention. In particular, vehicle verification is especially challenging on account of the heterogeneity of vehicles in color, size, pose, etc. Image based vehicle verification is usually addressed as a supervised classification problem. Specifically, descriptors using Gabor filters have been reported to show good performance in this task. However, Gabor functions have a number of drawbacks relating to their frequency response. The main contribution of this paper is the proposal and evaluation of a new descriptor based on the alternative family of log-Gabor functions for vehicle verification, as opposed to existing Gabor filter-based descriptors. These filters are theoretically superior to Gabor filters as they can better represent the frequency properties of natural images. In this paper the classifications is done using SVM and Random Forest. in this Random Forest will classify vehicle and non vehicle and Human on road. Whereas SVM deals with only vehicle and non vehicle.

Keywords: Gabor filter, log gabor filter, SVM, Random Forest, Gaussian shaped function

Edition: Volume 3 Issue 12, December 2014

Pages: 703 - 707

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How to Cite this Article?

P. Pradeep Kumar, I. Krishna Rao, "Log Gabor Filter Based Feature Detection in Image Verification Application", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB14479, Volume 3 Issue 12, December 2014, 703 - 707

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