Content-based image retrieval using a combination of color correlograms and edge direction histogram

A good content-based image retrieval must provide a robustness to the spatial changing problem of an image which causes from different acquisition, such as, zooming image, same image but different color, etc. These mentioned problems is the main cause to degrade the retrieval performance. To achieve the best retrieval result, an optimal feature must be invented to represent an image semantic. At present, instead of using single feature, most image retrieval system utilizes combining features between two low-level features in an image to retain high precision when faces to the mentioned problem. However, the retrieval error still remains. It causes from the combination of two unsuitable features. Thus, choosing two compatible features is another interested research issue in this area. This paper proposed a new feature combination between color correlograms and edge direction histogram (EDH) in order to give precedence to spatial information in an image. Using color correlogram will treat information about spatial color correlation, while EDH provides the geometry information in the case of the same image but different color. Performance evaluation performs by simple calculation like Euclidean Distance between the query image and image in the database. The experimental result shows that using this combining feature yields a good result while compares with the other combining scheme.