CAJ | 학술논문

为了有效地分割红外图像中的人体，提出了一种基于最大熵阈值的红外图像人体目标分割方法。对红外图像进行滤波处理消除噪声干扰，分别计算图像的目标熵和背景熵，最大化目标与背景熵的和，在目标和背景的分布中获得最大信息，以此为准则选择分割阈值。利用形态学方法进行后处理进一步消除噪声干扰。实验结果表明：与经典的阈值分割方法相比，文中方法效果更好，且运算速度快。
위료유효지분할홍외도상중적인체，제출료일충기우최대적역치적홍외도상인체목표분할방법。대홍외도상진행려파처리소제조성간우，분별계산도상적목표적화배경적，최대화목표여배경적적화，재목표화배경적분포중획득최대신식，이차위준칙선택분할역치。이용형태학방법진행후처리진일보소제조성간우。실험결과표명：여경전적역치분할방법상비，문중방법효과경호，차운산속도쾌。
The method for the pedestrian segmentation based on the maximum entropy threshold is presented in order to effectively segment the pedestrian in infrared images .The infrared image is filtered first to eliminate the noise effect .Then the object entropy and the background entropy are calculated respectively ,and the sum of entropies of object and background is maximized to obtain the maximum information from the object and background distributions in the image .According to the information the threshold is egmented .The final treatment is made by the morphological method to further eliminate the noise effect .Experimental results show that the proposed method has advantages over the existing classic thresholding methods of good segmentation quality and high calculation speed .