DocumentCode :
2149817
Title :
Gastroscopic Image Retrieval Based on PCA
Author :
Chen, Qin ; Tai, Xiaoying
Volume :
2
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
505
Lastpage :
509
Abstract :
Herein we describe a system for gastroscopic image retrieval which based on PCA algorithm. First quantize and cluster in HSV color space, make use of spatial partitioning-weighted method to calculate each block’s main color, and then combine with color correlogram to carry out integrate retrieval. A PCA algorithm is adopted to reduce the dimension since the dimension of feature vector which including color and spatial information is high. A prototype system which supports query by example is designed and implemented. The experimental results according to the prototype show that the approach proposed in the paper is effective to gastroscopic images.
Keywords :
Biomedical imaging; Clustering algorithms; Image retrieval; Information retrieval; Medical diagnostic imaging; Partitioning algorithms; Principal component analysis; Prototypes; Quantization; Signal processing algorithms; PCA algorithm; color correlogram; gastroscopic images; partitioning-weighted main color;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2008. CISP '08. Congress on
Conference_Location :
Sanya, China
Print_ISBN :
978-0-7695-3119-9
Type :
conf
DOI :
10.1109/CISP.2008.230
Filename :
4566355
Link To Document :
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