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An efficient face detection method using skin-color discovering and chain code

Ho K. I. J., Chen T. S., Cheng C. Y.

Machine Graphics and Vision

2002

Vol. 11, No. 2/3

241-256

In this paper, we propose a method to local human faces in color image. For color images, the skin color is an important key feature for human face detection. Thus, this paper applied skin color information to segmented human face areas: first, we reduce the size of the color image, hold its ratio, and detect skin color pixels in the resized image based on the properties of skin color. Next, our method employs the detected pixels and chain code to locate continuous areas. Finally, we check the width and the height of each located area, and filter out the non-facial ones. The remaining areas the human face regions. To fully explore the efficiency and effectiveness of the proposed method, we conduct a lot of experiments on the test image used in other papers. The experimental results show that both the false positive and false negative rates are eiter equal to or better than those obtained in previous research results. Moreover, in most of experiments, the processing time of our method is shorter.

Optimised black-and-white contour coding

Turner M. J.

Machine Graphics and Vision

2000

Vol. 9, No. 1/2

397-402

A hierarchical two-dimensional structural iamge segmentation algorithm based on a contour tree description is presented. This format is compared with more traditional facsimile coding standards (T.4, T.6 and T.82) (as well as other common compression standards) on the standard ITU test set of facsimile images. A detailed study of the coding complexity and choices required to design a general contour coding strategy is carried out. A final choice of parameters is presented and compared against previous work on gray-scale imagery.