A Robust Template Matching Algorithm Based on Reducing Dimensions

• 作者: Y. M. Fouda
• 来源期刊: 信号与信息处理(英文)
• 学科: 工学
• 关键词: Image Processing TEMPLATE MATCHING Vector SUM SUM of SQUARE DIFFERENCE
• 年，卷（期）: 2015,（2）
• 页码范围: 109-122
• 页数: 14页
• 分类号: TP39

摘要

Template matching is a fundamental problem in pattern recognition, which has wide applications, especially in industrial inspection. In this paper, we propose a 1-D template matching algorithm which is an alternative for 2-D full search block matching algorithms. Our approach consists of three steps. In the first step the images are converted from 2-D into 1-D by summing up the intensity values of the image in two directions horizontal and vertical. In the second step, the template matching is performed among 1-D vectors using the similarity function sum of square difference. Finally, the decision will be taken based on the value of similarity function. Transformation template image and sub-images in the source image from 2-D grey level information into 1-D information vector reduce the dimensionality of the data and accelerate the computations. Experimental results show that the computational time of the proposed approach is faster and performance is better than three basic template matching methods. Moreover, our approach is robust to detect the target object with changes of illumination in the template also when the Gaussian noise added to the source image.