利用互相关方法识别图片内容

Use Cross-correlation To Discern Content of An Image

图像内容识别是图像处理方向的一大难题,现有的图像内容识别方法大多都是用神经网络算法实现的,本文利用互相关的方法,从另一个角度对图像内容识别作了一个探索。互相关方法是通过一副已知的图像和未知图像作互相关计算,计算两副图像间的互相关程度,并以此说明两副图像的相似度,达到图像内容识别的目的。由于互相关值与图像本身大小存在一定关系,本文提出了互相关偏差的概念,利用两副图像间的互相关值和已知图像的自相关值的偏差程度,更准确地描述了两副图像间的相似偏差程度。实验结果表明,此方法能够准确地识别内容简单的图像。

It is a difficulty to discern the content of an image at the filed of Image Processing. The methods now used in most are implemented with the algorithm of Neural Network. This paper has made an exploration of determining the content of an image through another way that used the Cross-correlation of two images. To achieve the purpose, this algorithm computes the relation of two images to declare the similarity of them. Because of that the value is referenced with the size of these two images, a new con- cept named Deviation of Cross-correlation was produced in this paper. The Deviation of Cross-correlation made it more exact to descript the similarity. The experiment shows that this algorithm can discern the content of simple images exactly.