摘要
针对红外图像目标识别技术难的问题,提出了一种基于感兴趣区域的目标提取方法.首先利用二维最大熵方法检测红外图像中的感兴趣区域,在此基础上将局部分类方法应用于感兴趣区域中每一个像素点的局部邻域,以分析该像素的灰度特性;然后运用像素点的斜面距离构建该像素点的空间位置特性,并与灰度特性相结合;最后定义新的阈值判断方法进行像素归属性判断,以达到分离背景提取目标的效果.经实验验证,在红外目标提取技术上本文方法较经典的otsu方法和最大熵方法相比具有较高的准确性及稳定性,对于红外图像对比度低、识别难的问题具有一定的应用价值.
A target extraction method based on region of interest is presented to solve the difficult problem of infrared image target identification technology. Firstly, the regions of interest are detected by using two-dimensional maximum entropy method, on the basis of this, the local classification method is applied to the local neighborhood of each pixel in the region of interest, in order to analyse the pixel gray characteristics; Secondly, the spatial position characteristics of every pixel point is builded by calculation of chamfer distance, and is combined with the gray characteristic; Finally, the new determination method of threshold value is defined to fetermine the ownership of every pixel point, to achieve the separation of background and extraction of target. The results of experiments indicate that the proposed method has a higher accuracy and stability comparing with the classic otsu method and maximum entropy method in infrared target extraction, it has a certain value for problems of low contrast and difficult recognition of infrared image.
出处
《微电子学与计算机》
CSCD
北大核心
2013年第12期35-40,共6页
Microelectronics & Computer
关键词
目标提取
感兴趣区域
二维最大熵
局部分类
斜面距离
object extraction
region of interest
two-dimensional maximum entropy
local classification
chamfer distance
