Wavelet Local Feature (WLF) Pattern Recognition System

Abstract

In this paper is presented a pattern recognition methodology based on local feature extraction. The purpose of this system is to identify and locate, in three different scale pyramids, key points that represent relevant information of the image; this information is stored in a descriptor which is used to compares the key points of two images and know if they have similar information, or if they are the same images. This methodology uses the Haar wavelet transform to generate the three scale pyramids. This transform is used because it has several properties, such as noise elimination, multi-resolution analysis, and detection of diagonal, horizontal and vertical edges. The performance of this system was tasted using images with different scales and comparing the results with the Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) methodologies. The WLF system showed to has the highest percentage of correct point-matching.