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Proceedings Paper

Component-based target recognition inspired by human vision
Author(s): Yufeng Zheng; Kwabena Agyepong
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Paper Abstract

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

Paper Details

Date Published: 4 May 2009
PDF: 8 pages
Proc. SPIE 7335, Automatic Target Recognition XIX, 73350V (4 May 2009); doi: 10.1117/12.820074
Show Author Affiliations
Yufeng Zheng, Alcorn State Univ. (United States)
Kwabena Agyepong, Alcorn State Univ. (United States)

Published in SPIE Proceedings Vol. 7335:
Automatic Target Recognition XIX
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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