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Proceedings Paper

A new adaptive object detection technique based on the wavelet co-occurrence features
Author(s): Keivan Ashabi; Ali Mahmoodi; Elmira Vafabakhsh; Hamid Borji
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Paper 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.

Paper Details

Date Published: 9 July 2011
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80093J (9 July 2011); doi: 10.1117/12.896071
Show Author Affiliations
Keivan Ashabi, Malek Ashtar Univ. of Technology (Iran, Islamic Republic of)
Ali Mahmoodi, Malek Ashtar Univ. of Technology (Iran, Islamic Republic of)
Elmira Vafabakhsh, Malek Ashtar Univ. of Technology (Iran, Islamic Republic of)
Hamid Borji, Malek Ashtar Univ. of Technology (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)

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