Optimal Estimation of Contour Properties by Cross-Validated Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications
Integrating Region Growing and Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation using laser radar data
Pattern Recognition
The interpretation of laser radar images by a knowledge-based system
Machine Vision and Applications
Introduction to statistical signal processing with applications
Introduction to statistical signal processing with applications
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Image Segmentation by Unifying Region and Boundary Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
"Brownian Strings": Segmenting Images with Stochastically Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Game-Theoretic Integration for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale Segmentation of Three-Dimensional MR Brain Images
International Journal of Computer Vision
Isophotes Selection and Reaction-Diffusion Model for Object Boundaries Estimation
International Journal of Computer Vision
Color image segmentation using fuzzy C-means and eigenspace projections
Signal Processing
Strategies for image segmentation combining region and boundary information
Pattern Recognition Letters
Yet Another Survey on Image Segmentation: Region and Boundary Information Integration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Region-Boundary Cooperative Image Segmentation Based on Active Regions
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
From Parametric Warping to the Cooperation of Local Features and Global Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
An Integrated Approach for Surface Finding in Medical Images
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Seeded region growing: an extensive and comparative study
Pattern Recognition Letters
Vectorial scale-based fuzzy-connected image segmentation
Computer Vision and Image Understanding
Edge affinity for pose-contour matching
Computer Vision and Image Understanding
Region saliency as a measure for colour segmentation stability
Image and Vision Computing
Computers and Industrial Engineering
Technical Note: Multi-sensor data fusion of aerosol optical thickness
International Journal of Remote Sensing
Multi-sensor data fusion and comparison of total column ozone
International Journal of Remote Sensing
Vectorial scale-based fuzzy-connected image segmentation
Computer Vision and Image Understanding
Automatic seeded region growing for color image segmentation
Image and Vision Computing
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
A bayesian approach for weighting boundary and region information for segmentation
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Fuzzy sets theory based region merging for robust image segmentation
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
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We present an algorithm that integrates multiple region segmentation maps and edge maps. It operates independently of image sources and specific region-segmentation or edge-detection techniques. User-specified weights and the arbitrary mixing of region/edge maps are allowed. The integration algorithm enables multiple edge detection/region segmentation modules to work in parallel as front ends. The solution procedure consists of three steps. A maximum likelihood estimator provides initial solutions to the positions of edge pixels from various inputs. An iterative procedure using only local information (without edge tracing) then minimizes the contour curvature. Finally, regions are merged to guarantee that each region is large and compact. The channel-resolution width controls the spatial scope of the initial estimation and contour smoothing to facilitate multiscale processing. Experimental results are demonstrated using data from different types of sensors and processing techniques. The results show an improvement over individual inputs and a strong resemblance to human-generated segmentation.