Object detection based on improved color and scale invariant features

Mengyang Chen; Peng Fan

doi:10.1117/12.832493

30 October 2009 Object detection based on improved color and scale invariant features

Mengyang Chen, Peng Fan

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 749516 (2009) https://doi.org/10.1117/12.832493
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

A novel object detection method which combines color and scale invariant features is presented in this paper. The detection system mainly adopts the widely used framework of SIFT (Scale Invariant Feature Transform), which consists of both a keypoint detector and descriptor. Although SIFT has some impressive advantages, it is not only computationally expensive, but also vulnerable to color images. To overcome these drawbacks, we employ the local color kernel histograms and Haar Wavelet Responses to enhance the descriptor's distinctiveness and computational efficiency. Extensive experimental evaluations show that the method has better robustness and lower computation costs.

Citation Download Citation

Mengyang Chen and Peng Fan "Object detection based on improved color and scale invariant features", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 749516 (30 October 2009); https://doi.org/10.1117/12.832493

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