Title :
Automatic localization of human eyes in complex background
Author :
Tao, Liang ; Kwan, H.K.
Author_Institution :
Dept. of Electron. Eng. & Inf. Sci., Anhui Univ., Hefei, China
Abstract :
Based on geometrical facial features and image segmentation, this paper presents a novel algorithm for automatic localization of human eyes in grayscale still images with complex backgrounds. First of all, an eye location determination criterion is established by the a priori knowledge of geometrical facial features. Secondly, a range of threshold values that would separate eye blocks from others in a segmented facial image is estimated from the facial image histogram. Thirdly, with the progressive increase of the threshold by an appropriate step in that range, the size of the existing blocks in the segmented facial image will expand, some existing blocks will merge into one block, and some new blocks will emerge. Once two eye blocks appear from the segmented image, they will be detected by the eye location determination criterion. Finally, the 2D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. In this way, the optimal threshold value can be automatically found, based on the detection result, such that eyes can be accurately located. The experimental results demonstrate the high efficiency of the algorithm in runtime and its correct localization rate.
Keywords :
face recognition; feature extraction; image representation; image segmentation; optical correlation; symmetry; 2D correlation coefficient; algorithm localization rate; algorithm runtime efficiency; automatic face recognition system; automatic human eyes location; block merging; complex background images; eye block separation threshold values; eye detection factuality check; eye location determination criterion; facial image histogram; feature extraction; feature representation; geometrical facial features; grayscale still images; human eyes localization; image segmentation; segmented facial image block size; symmetry similarity measure; Eyes; Face detection; Face recognition; Facial features; Gray-scale; Histograms; Humans; Image segmentation; Information science; Pixel;
Conference_Titel :
Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium on
Print_ISBN :
0-7803-7448-7
DOI :
10.1109/ISCAS.2002.1010792