Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Adaptive mathematical morphology for edge linking
Information Sciences—Informatics and Computer Science: An International Journal
Graph Partitioning Active Contours (GPAC) for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rapid and Brief Communication: GACV: Geodesic-Aided C-V method
Pattern Recognition
Object segmentation using graph cuts based active contours
Computer Vision and Image Understanding
A geometric active contour model without re-initialization for color images
Image and Vision Computing
Color Image Segmentation Based on a New Geometric Active Contour Model
MVHI '10 Proceedings of the 2010 International Conference on Machine Vision and Human-machine Interface
Distance regularized level set evolution and its application to image segmentation
IEEE Transactions on Image Processing
Object Segmentation by Comparison of Active Contour Snake and Level Set in Biomedical Applications
BIBM '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine
Morphological gradient applied to new active contour model for color image segmentation
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region growing: a new approach
IEEE Transactions on Image Processing
Fuzzy homogeneity approach to multilevel thresholding
IEEE Transactions on Image Processing
Automatic image segmentation by integrating color-edge extraction and seeded region growing
IEEE Transactions on Image Processing
A Multiresolution Stochastic Level Set Method for Mumford–Shah Image Segmentation
IEEE Transactions on Image Processing
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In this paper, a novel level set approach is presented to segment only indicated objects from natural color images. To solve this challenging problem, users first initialize a contour inside the concerned object. The proposed level set model is then applied to achieve the object containing this initial region regardless of its shape and size. In our novel framework, the energy functional is a combination of two energy terms based on Bhattacharya flow and graph partitioning active contour. So that movement of the contour can be controlled toward object boundaries by correlative relationships between the interested region and surroundings. The experimental results obtained from our natural image collection show that the suggested method yields more accurate and better performance when comparing to other segmentation algorithms.