Comparing Intensity Transformations and Their Invariants in the Context of Color Pattern Recognition
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Spectro-Spatial Gradients for Color-Based Object Recognition and Indexing
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
Face Tracking Using the Dynamic Grey World Algorithm
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Illuminant and gamma comprehensive normalisation in log RGB space
Pattern Recognition Letters - Special issue: Colour image processing and analysis
A computer vision based human-robot interface
Autonomous robotic systems
Robust Histogram Construction from Color Invariants for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral gradients for color-based object recognition and indexing
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object matching in disjoint cameras using a color transfer approach
Machine Vision and Applications
An Algorithm to Determine the Chromaticity Under Non-uniform Illuminant
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
A convenient feature vector construction for vehicle color recognition
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
Bayesian 3D shape from silhouettes
Digital Signal Processing
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Most of the recent color recognition/indexing approaches concentr ate on establishing invariance to illumination color to improve the utility of color recognition. However, other effects caused by illumination pose and specularity on three-dimensional object surfaces have not received notable attention. We present a chromaticity recognition method that discounts the effects of illumination pose, illumination color and specularity. It utilizes a chromaticity space based on log-ratio of sensor responses for illumination pose and color invariance. A model-based specularity detection/rejection algorithm can be used to improve the chromaticity recognition and illumination estimation for objects including specular reflections.