Abstract
This paper presents an image block classification method using Tchebichef moments (TMs) and support vector machine (SVM). The test images are divided into non-overlapping 16 x 16 blocks and transformed into moment domain using Discrete Tchebichef Transform. These moment features are then used in the image content (block) classification. SVM is used for learning and classifying the blocks into three types: "plain", "edge" and "texture", based on their moment energy level. Experimental results show that the proposed method works well and the classification accuracy is 98.7%.
Original language | English |
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Title of host publication | ISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 409-412 |
Number of pages | 4 |
ISBN (Print) | 9781467363617 |
DOIs | |
Publication status | Published - 2013 |
Event | IEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2013 - Naha, Okinawa, Japan Duration: 12 Nov 2013 → 15 Nov 2013 https://ieeexplore.ieee.org/xpl/conhome/6691895/proceeding (Proceedings) |
Conference
Conference | IEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2013 |
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Abbreviated title | ISPACS 2013 |
Country/Territory | Japan |
City | Naha, Okinawa |
Period | 12/11/13 → 15/11/13 |
Internet address |