Title :
A Study on the Algorithm Based on Image Color Correlation Mining
Author :
Chen YongYue ; Xia Huosong
Author_Institution :
Dept. of Inf. Manage. & Inf. Syst., Wuhan Univ. of Sci. & Eng., Wuhan, China
Abstract :
Because of the semantic gap between low-level feature and high-level semantic feature of images, the results of the traditional color-based image retrieval canpsilat meet userspsila needs. In order to eliminate interference factors in the image retrieval, use image semantic feature and improve the accuracy of image retrieval, the paper introduces an algorithm based on the color correlation mining. It regards the pixel rows as a transaction set, uses the Apriori algorithm to find out the rows by looking for the continual co-occurrence color in the transaction set. These rows are correlative with the semantic object of the image. Then it extracts the correlative color histogram of image form the correlative color set to realize the correlative color mining.
Keywords :
correlation methods; data mining; feature extraction; image colour analysis; image retrieval; statistical analysis; Apriori algorithm; continual co-occurrence color; feature extraction; high-level semantic feature; histogram; image color correlation mining; image retrieval; interference factor elimination; low-level semantic feature; pixel row; semantic gap; transaction set; Data mining; Feature extraction; Histograms; Image retrieval; Information management; Information retrieval; Information security; Management information systems; Pixel; Quantization; Apriori algorithm; correlative color mining; image retrieve;
Conference_Titel :
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location :
Xian
Print_ISBN :
978-0-7695-3744-3
DOI :
10.1109/IAS.2009.143
