Image database retrieval utilizing affinity relationships
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Segmentation of black and white cartoons
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
Structural Method for Tracking Coronary Arteries in Coronary Cineangiograms
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Real-Time Imaging - Special issue on multi-dimensional image processing
Animation movies trailer computation
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Unsupervised multiscale segmentation of color images
Pattern Recognition Letters
Image histogram thresholding based on multiobjective optimization
Signal Processing
A high performance edge detector based on fuzzy inference rules
Information Sciences: an International Journal
EURASIP Journal on Applied Signal Processing
Non-supervised image segmentation based on multiobjective optimization
Pattern Recognition Letters
A robust approach to segment desired object based on salient colors
Journal on Image and Video Processing - Color in Image and Video Processing
A customized Gabor filter for unsupervised color image segmentation
Image and Vision Computing
Region-Oriented Visual Attention Framework for Activity Detection
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint
Modeling Attention and Perceptual Grouping to Salient Objects
Attention in Cognitive Systems
Colour image segmentation using homogeneity method and data fusion techniques
EURASIP Journal on Advances in Signal Processing - Image processing and analysis in biomechanics
Fuzzy filter based on interval-valued fuzzy sets for image filtering
Fuzzy Sets and Systems
Colorization of black-and-white cartoons
Image and Vision Computing
A new methodology for photometric validation in vehicles visual interactive systems
Proceedings of the 2010 ACM Symposium on Applied Computing
Distortion invariant road sign detection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Multivariate image segmentation using semantic region growing with adaptive edge penalty
IEEE Transactions on Image Processing
A study on multiple objects detection, loading and control in video for augmented reality
WSEAS Transactions on Computers
Fast defect detection in homogeneous flat surface products
Expert Systems with Applications: An International Journal
A methodology for photometric validation in vehicles visual interactive systems
Expert Systems with Applications: An International Journal
Modeling, evaluation and control of a road image processing chain
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Spatial homogeneity-based fuzzy c-means algorithm for image segmentation
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Querying web images by topic and example specification methods
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Automatic grayscale image colorization using histogram regression
Pattern Recognition Letters
Multiscale roughness measure for color image segmentation
Information Sciences: an International Journal
Fast image segmentation based on K-means algorithm
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Novel initialization scheme for Fuzzy C-Means algorithm on color image segmentation
Applied Soft Computing
Salient object detection based on regions
Multimedia Tools and Applications
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In this paper, a novel hierarchical approach to color image segmentation is studied. We extend the general idea of a histogram to the homogeneity domain. In the first phase of the segmentation, uniform regions are identified via multilevel thresholding on a homogeneity histogram. While we process the homogeneity histogram, both local and global information is taken into consideration. This is particularly helpful in taking care of small objects and local variation of color images. An efficient peak-finding algorithm is employed to identify the most significant peaks of the histogram. In the second phase, we perform histogram analysis on the color feature hue for each uniform region obtained in the first phase. We successfully remove about 99.7% singularity off the original images by redefining the hue values for the unstable points according to the local information. After the hierarchical segmentation is performed, a region merging process is employed to avoid over-segmentation. CIE(L*a*b*) color space is used to measure the color difference. Experimental results have demonstrated the effectiveness and superiority of the proposed method after an extensive set of color images was tested.