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Journal of Computational Physics
International Journal of Computer Vision
A Variational Method in Image Recovery
SIAM Journal on Numerical Analysis
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Coarse-to-Fine Deformable Contour Optimization Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Object detection using spatial histogram features
Image and Vision Computing
A logic framework for active contours on multi-channel images
Journal of Visual Communication and Image Representation
A novel real time system for facial expression recognition
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Unsupervised texture segmentation with nonparametric neighborhood statistics
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review
IEEE Transactions on Information Technology in Biomedicine
A general framework for low level vision
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A minimum entropy approach to adaptive image polygonization
IEEE Transactions on Image Processing
Wavelet-based level set evolution for classification of textured images
IEEE Transactions on Image Processing
Level set-based bimodal segmentation with stationary global minimum
IEEE Transactions on Image Processing
A disk expansion segmentation method for ultrasonic breast lesions
Pattern Recognition
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Small object detection in cluttered image using a correlation based active contour model
Pattern Recognition Letters
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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This paper investigates novel LBP-guided active contour approaches to texture segmentation. The local binary pattern (LBP) operator is well suited for texture representation, combining efficiency and effectiveness for a variety of applications. In this light, two LBP-guided active contours have been formulated, namely the scalar-LBP active contour (s-LAC) and the vector-LBP active contour (v-LAC). These active contours combine the advantages of both the LBP texture representation and the vector-valued active contour without edges model, and result in high quality texture segmentation. s-LAC avoids the iterative calculation of active contour equation terms derived from textural feature vectors and enables efficient, high quality texture segmentation. v-LAC evolves utilizing regional information encoded by means of LBP feature vectors. It involves more complex computations than s-LAC but it can achieve higher segmentation quality. The computational cost involved in the application of v-LAC can be reduced if it is preceded by the application of s-LAC. The experimental evaluation of the proposed approaches demonstrates their segmentation performance on a variety of standard images of natural textures and scenes.