基于边缘特征与HSI色彩特征的胸环靶弹孔识别

为解决胸环靶纸图像弹孔准确快速识别问题，提出结合弹孔边缘特征与色彩特征的胸环靶弹孔识别方法。采用形态学边缘检测算法确定胸环靶图像边缘，进行边缘图像增强处理，提高边缘图像与背景的对比度，提取弹孔区域色彩特征数据，实现胸环靶纸图像中弹孔识别。实验及计算分析结果表明：这种方法能准确从一次成像的胸环靶纸图像中进行弹孔提取，还能在一定程度上减少自然环境下光照、灰尘、振动对靶面图像造成的噪声、畸变影响。

Chest bitmap bullet identification based on edge feature and HSI color feature

In order to identify the chest bitmap bullet holes quickly and accurately through image processing, a new method, which combines bullet hole edge features with the HIS color space characteristics, is presented to realize the chest bitmap bullet holes identification. The chest bitmap bullet holes edge is determined and strengthened with the morphological edge detection algorithm, to improve the contrast between the holes edge image and the background. And then the color feature data is extracted to identify the bullet holes in the chest bitmap. Experiments and calculation results show that this method can be used to extract the bullet holes from just an imaging chest bitmap accurately, and to reduce the influence of image recognition effects from natural environment light, dust, distortion and the target image noise caused by vibration.