Fundamentals of digital image processing
Fundamentals of digital image processing
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Digital image processing
Encyclopedia of Artificial Intelligence
Encyclopedia of Artificial Intelligence
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Computer Vision
Data and Model-Driven Selection using Color Regions
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Image retrieval by color semantics
Multimedia Systems - Special issue on video content based retrieval
Recognition without Correspondence using MultidimensionalReceptive Field Histograms
International Journal of Computer Vision
Spatial Color Indexing and Applications
International Journal of Computer Vision
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Maintenance of Figure-Ground Segmentation
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
Recognizing Objects Using Color-Annotated Adjacency Graphs
Shape, Contour and Grouping in Computer Vision
Color-Based Pseudo Object Model for Image Retrieval with Relevance Feedback
AMCP '98 Proceedings of the First International Conference on Advanced Multimedia Content Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Relevance Feedback Techniques for Color-based Image Retrieval
MMM '98 Proceedings of the 1998 Conference on MultiMedia Modeling
Image Content-Based Retrieval Using Chromaticity Moments
IEEE Transactions on Knowledge and Data Engineering
Efficient matching of large-size histograms
Pattern Recognition Letters
Designing spectral sensitivity curves for use with Artificial Color
Pattern Recognition
Fast pattern recognition using normalized grey-scale correlation in a pyramid image representation
Machine Vision and Applications
Integrating spatial and color information in images using a statistical framework
Expert Systems with Applications: An International Journal
Fast min-hashing indexing and robust spatio-temporal matching for detecting video copies
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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We present a method to locate an 驴object驴 in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color distribution, which permits the use color-space processing. A new method is presented, which exploits more information than the previous Backprojection Algorithm of Swain and Ballard at a competitive complexity. Precisely, the new algorithm is based on matching local histograms with the model, instead of directly replacing pixels with a confidence that they belong to the object. We prove that a simple version of this algorithm degenerates into Backprojection in the worst case. In addition, we show how to estimate the scale of the model.Results are shown on pictures digitized from the famous 驴Where is Waldo驴 books. Issues concerning the optimal choice of a color space and its quantization are carefully considered and studied in this application. We also propose to use co-occurrence histograms to deal with cases where important color variations can be expected.