Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: A System for Region-Based Image Indexing and Retrieval
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
A novel log-based relevance feedback technique in content-based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Real-time computerized annotation of pictures
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
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This paper proposes an image retrieval system using the local and global properties of image regions. Colour features are extracted using the histograms of HSV colour space, texture features using Gray level Co-occurrence matrix (GLCM) and shape features using Edge Histogram Descriptors (EHD). The object regions are roughly identified by segmenting the image into fixed partitions and finding the white pixel density in each partition using edge thresholding and morphological dilation. To improve the retrieval efficiency, global colour and shape features are also taken into account. Euclidean distance measure is used for computing the distance between the features of the query and target image. An automatic relevance feedback algorithm is also proposed for improving the retrieval accuracy. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.