Image texture representation and retrieval based on power spectral histograms

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Volumn , Issue , 2004, Pages 491-495

  Wang, Chong Jun ^a   Yang, Yu Bin ^a   Li, Wu Jun ^a   Chen, Shi Fu ^a  

^a NANJING UNIVERSITY   (China)

Author keywords

Co occurrence matrix; Content based image retrieval; Similarity measurement; Texture extraction

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; IMAGE ANALYSIS; MATRIX ALGEBRA; STATISTICAL METHODS;

CO-OCCURRENCE MATRIX; SIMILIARITY MEASUREMENT; SPACE DOMAIN; TEXTURE EXTRACTION;

CONTENT BASED RETRIEVAL;

EID: 16244405253     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Smith J R. Image retrieval evaluation. IEEE Workshop on Content-based Access of Image and Video Libraries. Santa Barbara, California, 1998: 112-113
2. Haralick, R.M., Shanmugam, K., and Dinstein, I. Texture features for image classification. IEEE Transactions on Systems, Man and Cybernetics, Vol. 3, 1973(6): 768-780.
3. Yang Yubin. Research and Application on the key techniques of Content-based Image Retrieval [Ph. D. Thesis]. Nanjing: Nanjing University, 2003 (in Chinese with English Abstract).
4. Ma W Y, Zhang H J. Benchmarking of image features for content-based retrieval. In: Proc. 32nd Asilomar Conference on Signals, Systems and Computers, California, US, January 1998: 253-257
5. Stone H S, Li C S. Image matching by means of intensity and texture matching in the Fourier domain. In: Proc. SPIE: Storage and Retrieval for Image and Video Databases IV, Vol. 2670, 1996: 337-349
6. Augusteijn M, Clemens L E, Shaw K A. Performance evaluation of texture measures for ground cover identification in satellite images by means of a neural network classifier. IEEE Transactions on Geosciences and Remote Sensing, Vol. 33, 1995(5): 616-626