Natural / Man-Made Object Classification Based on Gabor Characteristics

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• 作者：Minhwan Kim ; Changmin Park ; Kyongmo Koo
• 刊名：Lecture Notes in Computer Science
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：3568
• 期：1
• 页码：p.550
• 全文大小：552 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Recently many researchers are interested in objects of interest in an image, which are useful for efficient image matching based on them and bridging the semantic gap between higher concept of users and low-level image features. In this paper, we introduce a computational approach that classifies an object of interest into a natural or a man-made class, which can be of great interest for semantic indexing applications processing very large image databases. We first show that Gabor energy maps for man-made objects tend to have dominant orientation features through analysis of Gabor filtering results for many object images. Then a sum of Gabor orientation energy differences is proposed as a classification measure, which shows a classification accuracy of 82.9% in a test with 2,600 object images.