A PCNN improved with fisher criterion for infrared human image segmentation

Jiayuan Min, Yi Chai
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引用次数: 5

Abstract

Infrared human image is not enough contrasted, and gray overlap between background and human targets. A PCNN improved with Fisher criterion image method is proposed for these problems. The fisher criterion-based segmentation method achieve good segmentation in low image contrast. PCNN segmentation method is suitable for image with gray overlap between object and background. Combined these two method solves these two problems. Setting up dynamic threshold weight factor solves under-segmentation and over-segmentation problem of human body infrared image. Results show our method outperforms classical methods in terms of segmentation effect and rate.
基于fisher准则的PCNN红外人体图像分割
红外人体图像对比度不够,背景与人体目标之间存在灰度重叠。针对这些问题,提出了一种基于Fisher准则图像法的PCNN改进算法。基于fisher准则的分割方法在图像对比度较低的情况下实现了较好的分割。PCNN分割方法适用于目标与背景灰度重叠的图像。这两种方法的结合解决了这两个问题。建立动态阈值权重因子,解决了人体红外图像分割不足和分割过度的问题。结果表明,该方法在分割效果和分割率方面都优于经典方法。
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