Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semantic Video Object Segmentation for Content-Based Multimedia Applications
Semantic Video Object Segmentation for Content-Based Multimedia Applications
Multiresolution Color Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Evaluation of Image Segmentation Application to Multi-spectral Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing clusterings: an axiomatic view
ICML '05 Proceedings of the 22nd international conference on Machine learning
A color image segmentation approach for content-based image retrieval
Pattern Recognition
Object segmentation using ant colony optimization algorithm and fuzzy entropy
Pattern Recognition Letters
A novel approach for edge detection based on the theory of universal gravity
Pattern Recognition
Color reduction based on ant colony
Pattern Recognition Letters
Unsupervised segmentation of natural images via lossy data compression
Computer Vision and Image Understanding
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
An artificial ant colonies approach to medical image segmentation
Computer Methods and Programs in Biomedicine
Automatic joint classification and segmentation of whole cell 3D images
Pattern Recognition
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Computers & Mathematics with Applications
Short communication: An evaluation metric for image segmentation of multiple objects
Image and Vision Computing
Automatic seeded region growing for color image segmentation
Image and Vision Computing
3-D object segmentation using ant colonies
Pattern Recognition
Unsupervised colour image segmentation using dual-tree complex wavelet transform
Computer Vision and Image Understanding
A gravitational approach to edge detection based on triangular norms
Pattern Recognition
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Multiregion Image Segmentation by Parametric Kernel Graph Cuts
IEEE Transactions on Image Processing
Segmentation of color images using a linguistic 2-tuples model
Information Sciences: an International Journal
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In this paper, a novel image segmentation algorithm based on the theory of gravity is presented, which is called as ''stochastic feature based gravitational image segmentation algorithm (SGISA)''. The proposed SGISA uses color, texture, and spatial information to partition the image into homogenous and semi-compact segments. The proposed method benefits from the advantages of both clustering and region growing image segmentation techniques. The SGISA is equipped with a new operator called ''escape'' that is inspired by the concept of escape velocity in physics. Moreover, motivated by heuristic search algorithms, we incorporate a stochastic characteristic with the SGISA, which gives algorithm the ability to search the image for finding the fittest regions (pixels) that are suitable for merging. Several experiments on various standard images as well as Berkley standard image database are reported. Results are compared with a well-known clustering based segmentation method, C-means, a gravitational based clustering method (SGC), and the well-known mean-shift method. The results are reported using unsupervised criteria and pre-ground-truthed measures. The obtained results confirm the effectiveness of the proposed method in color image segmentation.