A novel image recognition method based on feature-extraction vector scheme

This paper introduces a method for recognizing images using a new approach to expressing images as vectors. Using this expression method, an image is constructed from 2 types of vectors - vectors indicating positions and vectors denoting intensity gradients for those positions. When investigating the amount of difference between two images, similarities are evaluated by calculating voting densities in the image space, using the vectors making up the sample image in relation to the vectors expressing the reference image. The expression proposed is invariant to image rotation and, by changing the resolution hierarchically, recognition using this expression is also adaptable to perspective and detail. Using this method, we carried out experimentation recognizing representative images from various fields and the results show that the method is effective in discriminating between them.