Comparative Analysis of Content Based Image Retrieval Techniques Using Color Histogram: A Case Study of GLCM and K-Means Clustering

Content based image retrieval is an active research issue that had been famous from 1990s till present. The main target of CBIR is to get accurate results with lower computational time. This paper discusses on the comparative method used in color histogram based on two major methods used frequently in CBIR which are; normal color histogram using GLCM, and color histogram using KMeans. A set of 9960 images are used to test the accuracy and the precision of each methods. Using Euclidean distance, similarity between queried image and the candidate images are calculated. Experiment results shows that color histogram with K-Means method had high accuracy and precise compared to GLCM. Future work will be made to add more features that are famous in CBIR which are texture, color, and shape features in order to get better results.