Title :
2-D functional AR model for image identification
Author :
Haseyama, Miki ; Kondo, Isao
Author_Institution :
Graduate Sch. of Eng., Hokkaido Univ., Sapporo, Japan
Abstract :
This paper proposes a 2D functional AR model for image identification. The definition of the proposed model includes functions that can exploit the self-similarity nature in images to thoroughly extract image features. By introducing the functional scheme into the model, only a small number of parameters, which are called 2D functional AR parameters, can describe the image features simply and accurately. These characteristics make the model suitable for image identification applications. Some experiments of image identification are performed, and the results verify that the proposed model accurately represents the image feature, and the image can be correctly identified. The calculation time is fast enough for practical use in image retrieval.
Keywords :
autoregressive processes; feature extraction; fractals; image coding; image representation; image retrieval; 2D functional AR model; calculation time; image feature extraction; image feature representation; image identification; image retrieval; self-similarity nature; Bandwidth; Content based retrieval; Digital recording; Feature extraction; Image databases; Image processing; Image retrieval; Image storage; Information retrieval; Integrated circuit modeling;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1199547