基于最大多符号信息熵的织物图像匹配

为了实现利用机器视觉技术识别织物图案的组成 ,对织物图案进行研究。依据熵函数是一个连续函数 ,且具有极值性 ,将其运用到图像检测与匹配中。把织物图像中的每一点作为单符号信源 ,整幅图像作为多符号信源 ,在织物成品图像上选取和基准样图尺寸大小相同的图像计算信息熵 ,若与样品图的信息熵相等 ,则说明在织物成品图中检测到样图 ,否则没有。实验结果表明该方法在织物图案匹配中是一种实用和成功的方法。

Matching of textile image based on the biggest multi-symbol information entropy

Detecting the composing of the textile image by using machine vision technology.The matching way of textile image was researched.The entropy function is a continuous function and has extreme property.The biggest multi\|symbol information entropy was applied into the detection and matching of fabric images,each point in an image was considered as a one\|symbol source,the whole image was considered as multi\|symbol source.The information entropy of the selected sub\|image in the textile image of finished product which has the same size as the standard sub\|image was calculated.If the information entropy of the selected sub\|image was equal to that of the standard image,the standard sub\|image was detected from the textile image,otherwise the standard sub\|image was not detected.The experimental results indicate that method is efficient and practicable.