Shape classification based on singular value decomposition transform

• 作 者: SHAABAN Zyad ARIF Thawar BABA
• 机 构: Faculty of Information Technology Applied Science University
• 出 处: 重庆邮电大学学报
• 发表日期: 2004年期
• 关键词: shape classification distance transformation nearest neighbor classifier moment
• 基金项目: cost of its publication from the Deanship of Research and Graduate Studies at Applied Science University, Amman, Jordan

In this paper, a new shape classification system based on singular value decomposition (SVD) transform using nearest neighbour classifier was proposed. The gray scale image of the shape object was converted into a black and white image. The squared Euclidean distance transform on binary image was applied to extract the boundary image of the shape. SVD transform features were extracted from the the boundary of the object shapes. In this paper, the proposed classification system based on SVD transform feature extraction method was compared with classifier based on moment invariants using nearest neighbour classifier. The experimental results showed the advantage of our proposed classification system.