The Conceptual Development Of Semantic-Based Image Retrieval And Indexing (CBR) Large Object Databases

Nor Mas Aina, Md Bohari and Intan Ermahani, A. Jalil and Amir Syarifuddin, Kasim (2009) The Conceptual Development Of Semantic-Based Image Retrieval And Indexing (CBR) Large Object Databases. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Content Based Image Retrieval (CBIR) is the retrieval of images based on visual features such as color, texture, and shape. In many large image databases, traditional methods of image indexing, ranging from storing !ill image in the database and associating it with a keyword or number, to associating it with a categorized description, have proven to be insufficient. laborious, and extremely time consuming. Whereas in CBlR, each image that is stored in the database has its features extracted and compared to the features of the query image. With this theory this research project is proposed. This research presents the theoretical concept and design of image feature extraction by using selected hybrid image feature extraction techniques; the combination of Scale-Invariant Feature Transform (SlFT), Elastic Bucket Tries (EBT) and Fuzzy-Rule Based (FRB) techniques. We show the advantages and disadvantages of the combination of those techniques in extracting and classifying the images based on different categories (tested for indoor room images). The proposed indoor images style was Malay, Chinese and Indian. The result is hoped to contribute a significant idea to the development of technology in classifying the indoor room images based on other styles such as Bali, English etc.

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