2-D Shape Classification Using Hidden Markov Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
A simplified approach to the HMM based texture analysis and its application to document segmentation
Pattern Recognition Letters
Belief networks, hidden Markov models, and Markov random fields: a unifying view
Pattern Recognition Letters - special issue on pattern recognition in practice V
Digital Image Processing
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
ImageRover: A Content-Based Image Browser for the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Image Database Retrieval of Rotated Objects by User Sketch
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Symmetry-Based Indexing of Image Databases
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Similarity Queries in Image Databases
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
New Improved Feature Extraction Methods for Real-Time High Performance Image Sequence Recognition
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Color image retrieval based on hidden Markov models
IEEE Transactions on Image Processing
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An integrated approach to shape and color-based image retrieval, where the cues color and shape are both utilized in a local rather than a global way, is presented in this paper. An experimental retrieval system has been developed, which enables the user to search a color image database intuitively for presenting simple sketches. In order to be able to perform an elastic matching, which is especially needed in sketch-based image retrieval, objects in the images are represented by Hidden Markov Models. The use of streams (sets of features that are assumed to be statistically independent) within the HMM framework allows the integration of shape and color derived features into a single model, thereby allowing to control the influence of the different streams via stream weights. The approach has been evaluated on a color image database containing 120 different isolated objects with arbitrary orientation and showed good retrieval results with several users. Futhermore, the use of HMMs allows efficient pruning and thus a fast retrieval even with large databases.