A content based image retrieval system for marine life images

Malaysia has been recognized as one of the twelve nations endowed with rich biodiversity. Such huge number of species in the rain forest and sea are an important asset that need to be properly documented. Responding to these important needs, we have designed and evaluated a content based image retrieval system catered for marine life images. This paper investigates the effectiveness of various low level image descriptors, which includes the colour, shape and texture features in representing the semantic categories of the marine life images. This is a challenging task since the images are taken from different viewpoints and marine species do not possess consistent colour, shape and textural appearance. For the purpose of evaluating the overall image retrieval system effectiveness, we design and implement an image retrieval system which support image query by example. Experiment is conducted to evaluate the effectiveness of various low level image descriptors and the fusion of multiple features. The experiment result on the image retrieval performance is presented.