Color Features and Color Spaces Applications to the Automatic Image Annotation

Abstract

Nowadays images play a crucial role in different fields such as medicine, advertisement, education and entertainment. Describing images content and retrieving them are important fields in image processing. Automatic image annotation is a process which produces words from a digital image based on the content of this the image by using a computer. In this chapter, after an introduction to neighbor voting algorithm for image annotation, we discuss the applicability of color features and color spaces in automatic image annotation. We discuss the applicability of three color features (color histogram, color moment and color Autocorrelogram) and three color spaces (RGB, HSI and YCbCr) in image annotation. Experimental results, using Corel5k benchmark annotated images dataset, demonstrate that using different color spaces and color features helps to select the best color features and spaces in image annotation area.