Content-Based Image Retrieval for Blood Cells

The rapid development of technologies and steadily growing amounts of digital information highlight the need of developing an accessing system. Content-based image indexing and retrieval has been an important research area in computer science for the last few decades. The approaches of content-based image retrieval using low level features such as colour, shape and texture are investigated to create a prototype that perceives blood cell images similar to a human. The histogram of red, green, and blue colour components is analyzed. The wavelet decomposition is also used to analyze texture. In addition, morphological operations such as opening and closing are applied to analyze object shape. Lastly, colour, texture, and shape in image retrieval are integrated in order to increase the retrieval accuracy. Experimental results using four different classes of 150 blood cell images showed 95.68% of retrieval accuracy.