An Improved Normalization Method for Haar-like Features for Real-time Object Detection 


Vol. 36,  No. 8, pp. 505-515, Aug.  2011


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  Abstract

This paper describes a normalization method of Haar-like features used for object detection. Previous method which performs variance normalization on Haar-like features requires a lot of calculations, since it uses an additional integral image for calculating the standard deviation of intensities of pixels in a candidate window and increases possibility of false detection in the area where variance of brightness is small. The proposed normalization method can be performed much faster than the previous method by not using additional integral image and classifiers which are trained with the proposed normalization method show robust performance in various lighting conditions. Experimental result shows that the object detector which uses the proposed method is 26% faster than the one which uses the previous method. Detection rate is also improved by 5% without increasing false alarm rate and 45% for the samples whose brightness varies significantly.

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  Cite this article

[IEEE Style]

K. Park and S. Hwang, "An Improved Normalization Method for Haar-like Features for Real-time Object Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 8, pp. 505-515, 2011. DOI: .

[ACM Style]

Ki-Yeong Park and Sun-Young Hwang. 2011. An Improved Normalization Method for Haar-like Features for Real-time Object Detection. The Journal of Korean Institute of Communications and Information Sciences, 36, 8, (2011), 505-515. DOI: .

[KICS Style]

Ki-Yeong Park and Sun-Young Hwang, "An Improved Normalization Method for Haar-like Features for Real-time Object Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 8, pp. 505-515, 8. 2011.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880