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Object Detection with Gabor Filters and Cumulative Histograms
Barcelona, Spain September 03-September 08
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.90548415th International Conference on Patt ...
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This paper proposes an algorithm for segmentation and extracting an object region by using Gabor filters. Gabor filters are exploited to extract spatial frequency in some orientations, and not only the outputs of Gabor filters but also color information are used to construct the features at each image pixel. The criterion is devised to consider the similarity, the region size and the region shape factors in order to efficiently merge the features. In general, a complex object may be segmented into multiple regions. However, for purpose of detecting such complex object, we represent the object region by the normalized cumulative histogram of features. From experimental results, it is found that the proposed algorithm is able to efficiently detect the object regions such as cars in images of usual traffic scenes.
Citation:
Tadayoshi Shioyama, Hai Yuan Wu, Shigetomo Mitani, "Object Detection with Gabor Filters and Cumulative Histograms," icpr, vol. 1, pp.1704, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 1, 2000
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