A note on the gradient of a multi-image
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
International Journal of Computer Vision
Frequency-Based Nonrigid Motion Analysis: Application to Four Dimensional Medical Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
A scheme of colour image retrieval from databases
Pattern Recognition Letters
Digital Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Pedestrian Recognition Using Real-time Motion Analysis
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume II
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
IEEE Transactions on Image Processing
Combining color and spatial information for object recognition across illumination changes
Pattern Recognition Letters
Color histograms adapted to query-target images for object recognition across illumination changes
EURASIP Journal on Applied Signal Processing
Color texture analysis using CFA chromatic co-occurrence matrices
Computer Vision and Image Understanding
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In the context of image indexing for the purpose of retrieval , colored object recognition methods tend to fail when the illumination of the objects varies from an image to another. A new approach to indexing images of persons is proposed, which copes with the variations of the lighting conditions. We assume that illumination changes can be described using a simple linear transform. For comparing two images, we transform the colors of the target one according to the colors of the query one by means of an original color histogram specification based on color invariant evaluation. For the retrieval purpose, we evaluate invariant color signatures of the query image and the transformed target image through the use of color co-occurrence matrices. Tests on real images are very encouraging, with substantially better results than those obtained with other well-established indexing and retrieval schemes.