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[Formula: see text][Formula: see text]), a medium-intensity region (0.25–0.75[Formula: see text][Formula: see text]), and a high-intensity region (0.75–1[Formula: see text][Formula: see text]), and then the intensity [Formula: see text] which satisfies the [Formula: see text] is selected as an intensity-level value [Formula: see text], and the intensity [Formula: see text] which satisfies [Formula: see text] is selected as an intensity-level value [Formula: see text], at last [Formula: see text] 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.

中文翻译：

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灰度红外图像中人体区域分割的强度因子法

本文定义了基于灰度图像统计一阶矩的归一化强度因子。强度因子可用于区分灰度图像的亮度水平，并确定图像分割的阈值。根据灰度红外图像中的强度因子和人体特征，设计了一种计算强度阈值的新算法，可用于红外图像中人体区域的分割。该算法基于强度因子的概念，将低亮度灰度图像（LGIRI）的直方图分为三部分：低强度区域（0.25[公式：见正文][公式：见正文]） ，中等强度区域（0.25-0.75[公式：见正文][公式：见正文]）和高强度区域（0.75-1[公式：见文][公式：见文]），然后选择满足[公式：见文]的强度[公式：见文]作为强度等级值[公式：见文]，强度[公式：见文] :see text]满足[Formula:see text]被选为强度级别值[Formula:see text]，最后[Formula:see text]为像素分类阈值（强度级别阈值）。需要注意的是，没有图像噪声过滤和/或处理的预处理，所有图像均来自 OTCBVS。与选取直方图波谷点作为强度级别阈值的方法相比，该算法避免了直方图高强度级别不存在明显波谷点的问题。还，