Intensity Factor Method for Segmenting Human Body Region in Gray-scale Infrared Image.

The normalized intensity factor based on statistical first-order moment of gray-scale image is defined in this paper. The intensity factor can be used to distinguish the brightness level of a gray-scale image and to determine a threshold value for image segmentation. According to the intensity factor and the characteristic of human body in the gray-scale infrared image, a new algorithm of calculating the intensity-level threshold is designed which can be used for segmenting human body area in an infrared image. In the algorithm, based on the concept of intensity factor, a histogram of low brightness gray-scale image (LGIRI) is divided into three parts: a low-intensity region (0.25 L), a medium-intensity region (0.25–0.75 L), and a high-intensity region (0.75–1 L), and then the intensity i which satisfies the L a M (i) = 0. 5 k L L a is selected as an intensity-level value k h , and the intensity i which satisfies L M (i) = 0. 5 k L L is selected as an intensity-level value t h , at last 0. 5 (t h + k h) is the pixel classification threshold (the intensity-level threshold). It is noted that there is no preprocessing for image noise filtering and/or processing, and all images come from OTCBVS. Compared with the method of selecting trough points of the histogram as the intensity-level threshold, this algorithm avoids the problem of nonexistence of evident trough point at the high-intensity level of a histogram. Also, the experimental results show that the segmenting results of LGIRI processed by the algorithm are better than those of Otsu method. [ABSTRACT FROM AUTHOR]