A new adaptive object detection technique based on the wavelet co-occurrence features

Keivan Ashabi; Ali Mahmoodi; Elmira Vafabakhsh; Hamid Borji

doi:10.1117/12.896071

8 July 2011 A new adaptive object detection technique based on the wavelet co-occurrence features

Keivan Ashabi, Ali Mahmoodi, Elmira Vafabakhsh, Hamid Borji

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80093J (2011) https://doi.org/10.1117/12.896071
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

This Object detection involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an adaptive algorithm for detecting a specified target objects embedded in visual images for tracking application. The developed algorithm employs a novel technique using the wavelet co-occurrence features for detecting object based on template matching. Several signatures as contrast, energy, entropy and maximum probability are computed from wavelet co-occurrence features for object window and compares with features of image windows. The results of the proposed algorithm are very adaptive in variant condition with clutters.

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Keivan Ashabi, Ali Mahmoodi, Elmira Vafabakhsh, and Hamid Borji "A new adaptive object detection technique based on the wavelet co-occurrence features", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80093J (8 July 2011); https://doi.org/10.1117/12.896071

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KEYWORDS

Wavelets

Feature extraction

Matrices

Target detection

Detection and tracking algorithms

Algorithm development

Optical tracking

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