Title :
A Bayesian network approach for image similarity
Author :
Herdiyeni, Yeni ; Pebuardi, Rizki ; Buono, Agus
Author_Institution :
Dept of Comput. Sci., Bogor Agric. Univ., Bogor, Indonesia
Abstract :
This paper proposed Bayesian Network approach for image similarity measurement based on color, shape and texture. Bayesian network model can determine dominant information of an image using occurrence probability of image´s characteristics. This probability is used to measure image similarity. Performance of the system is determined using recall and precision. Based on experiment, Bayesian network model can improve performance of image retrieval system. Experiment result showed that the average precision gain up of using Bayesian network model is about 8.28%. The average precision of using Bayesian network model is better than using color, shape, or texture information individually.
Keywords :
belief networks; image colour analysis; image retrieval; image texture; Bayesian network; color information; image retrieval system; image similarity measurement; occurrence probability; shape information; texture information; Bayesian methods; Feature extraction; Histograms; Image analysis; Image color analysis; Image databases; Image retrieval; Performance analysis; Pixel; Shape measurement; Bayesian network; co-occurrence matrix; edge direction histogram; histogram-162;
Conference_Titel :
Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME), 2009 International Conference on
Conference_Location :
Bandung
Print_ISBN :
978-1-4244-4999-6
Electronic_ISBN :
978-1-4244-5000-8
DOI :
10.1109/ICICI-BME.2009.5417298