IRM: integrated region matching for image retrieval
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
A New and Effective Image Retrieval Method Based on Combined Features
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Compact Composite Descriptors for Content Based Image Retrieval: Basics, Concepts, Tools
Compact Composite Descriptors for Content Based Image Retrieval: Basics, Concepts, Tools
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We propose Content-Based Image Retrieval (CBIR) system using local RGB colour and texture features. Firstly, the image is divided into sub-blocks, and then the local features are extracted. Colour is represented by Colour Histogram (CH) and Colour Moment (CM). Texture is obtained by using Gabor filter (Gab) and Local Binary Pattern (LBP). An integrated matching scheme based on Most Similar Highest Priority (MSHP) principle is used to compare the blocks of query and database image. Since each feature extracted from images just characterizes certain aspect of image content, features fusion are necessary to increase the retrieval performance. We present a novel fusion method based on fusing the distance value for each feature instead of the feature itself to avoid the curse of dimensionality. Experimental results in terms of the precision/recall estimates demonstrate that the performance of the proposed fusion method gives better performance than that when either method is used alone.