Iconic pictorial retrieval using multiple attributes and spatial relationships
Knowledge-Based Systems
Region-based fit of color homogeneity measures for fuzzy image segmentation
Fuzzy Sets and Systems
Retrieving images in fuzzy object-relational databases using dominant color descriptors
Fuzzy Sets and Systems
An Image Retrieval System Based on the Color, Areas, and Perimeters of Objects
Fundamenta Informaticae
Fuzzy homogeneity measures for path-based colour image segmentation
International Journal of Intelligent Systems Technologies and Applications
A ROI image retrieval method based on CVAAO
Image and Vision Computing
About the Embedding of Color Uncertainty in CBIR Systems
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Fuzzy color histogram-based video segmentation
Computer Vision and Image Understanding
An efficient region-based image representation using Legendre color distribution moments
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Stratification-based keyframe cliques for removal of near-duplicates in video search results
Proceedings of the international conference on Multimedia information retrieval
An image retrieval system based on colors and shapes of objects
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Perimeter intercepted length and color t-value as features for nature-image retrieval
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
A statistical image retrieval method using color invariant
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Robust image retrieval based on color histogram of local feature regions
Multimedia Tools and Applications
Digital video scenes identification using audiovisual features
WebMedia '09 Proceedings of the XV Brazilian Symposium on Multimedia and the Web
Local-global neuro-fuzzy system for color change modelling
International Journal of Hybrid Intelligent Systems - Advances in Intelligent Agent Systems
Exploiting local dependencies with spatial-scale space (S-Cube) for near-duplicate retrieval
Computer Vision and Image Understanding
An analytic distance metric for Gaussian mixture models with application in image retrieval
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Kernel-based object tracking using a simple fuzzy color histogram
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Ranking by k-means voting algorithm for similar image retrieval
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
An Image Retrieval System Based on the Color, Areas, and Perimeters of Objects
Fundamenta Informaticae
Robust color image retrieval using visual interest point feature of significant bit-planes
Digital Signal Processing
| Hi-index | 0.01 |
A conventional color histogram (CCH) considers neither the color similarity across different bins nor the color dissimilarity in the same bin. Therefore, it is sensitive to noisy interference such as illumination changes and quantization errors. Furthermore, CCHs large dimension or histogram bins requires large computation on histogram comparison. To address these concerns, this paper presents a new color histogram representation, called fuzzy color histogram (FCH), by considering the color similarity of each pixel's color associated to all the histogram bins through fuzzy-set membership function. A novel and fast approach for computing the membership values based on fuzzy c-means algorithm is introduced. The proposed FCH is further exploited in the application of image indexing and retrieval. Experimental results clearly show that FCH yields better retrieval results than CCH. Such computing methodology is fairly desirable for image retrieval over large image databases.