Computational geometry: an introduction
Computational geometry: an introduction
Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graphical Models and Image Processing
Fast noise variance estimation
Computer Vision and Image Understanding
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape measures for content based image retrieval: a comparison
Information Processing and Management: an International Journal
The Tractability of Segmentation and Scene Analysis
International Journal of Computer Vision
Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
Image classification and querying using composite region templates
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Retrieval of images of man-made structures based on projective invariance
Pattern Recognition
Evaluation of VISTO: a new vector image search tool
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
VISTO: A new CBIR system for vector images
Information Systems
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One of the main goals in content-based image retrieval is to incorporate shape into the process in a reliable manner. In order to overcome the difficulties of directly obtaining shape information (in particular avoiding region segmentation) we develop several shape measures that tackle the problem in an indirect manner, requiring only a minimal amount of segmentation. A histogram-based scheme is then used, maintaining low complexity with high efficiency and robustness. The obtained results showed that the combination of the shape measures provide an improvement over the colour histogram.