Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
Hierarchy in Picture Segmentation: A Stepwise Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Digital topology: introduction and survey
Computer Vision, Graphics, and Image Processing
Segmentation of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance study of several global thresholding techniques for segmentation
Computer Vision, Graphics, and Image Processing
Hierarchical Image Analysis Using Irregular Tessellations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A common framework for image segmentation
International Journal of Computer Vision
Computer vision, models and inspection
Computer vision, models and inspection
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Segmentation of X-ray and C-scan images of fiber reinforced composite materials
Pattern Recognition
Automatic threshold selection using the wavelet transform
CVGIP: Graphical Models and Image Processing
Variational methods in image segmentation
Variational methods in image segmentation
Objective and quantitative segmentation evaluation and comparison
Signal Processing
Multicolor well-composed pictures
Pattern Recognition Letters
Computer Vision and Image Understanding
On detection and representation of multiscale low-level image structure
ACM Computing Surveys (CSUR)
Recognition of 2D Object Contours Using the Wavelet Transform Zero-Crossing Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital connectivity and extended well-composed sets for gray images
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Connectivity in Digital Pictures
Journal of the ACM (JACM)
Connected filtering and segmentation using component trees
Computer Vision and Image Understanding
Scale-based fuzzy connected image segmentation: theory, algorithms, and validation
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Encoding Visual Information Using Anisotropic Transformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimum Image Thresholding via Class Uncertainty and Region Homogeneity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Vision
Artificial Neural Networks for Computer Vision
Artificial Neural Networks for Computer Vision
SIGMA: A Knowledge-Based Aerial Image Understanding System
SIGMA: A Knowledge-Based Aerial Image Understanding System
Digital Picture Processing
Image Representation Via a Finite Radon Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
A theory of parameter-dependent connected components of gray images and segmentation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
The fuzzy geometry of image subsets
Pattern Recognition Letters
Grey level thresholding using second-order statistics
Pattern Recognition Letters
A recursive thresholding technique for image segmentation
IEEE Transactions on Image Processing
Region growing: a new approach
IEEE Transactions on Image Processing
Image segmentation and labeling using the Polya urn model
IEEE Transactions on Image Processing
Thresholding using two-dimensional histogram and fuzzy entropy principle
IEEE Transactions on Image Processing
Automatic image segmentation by integrating color-edge extraction and seeded region growing
IEEE Transactions on Image Processing
The Khoros software development environment for image and signal processing
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
In this paper, we propose a method for understanding an image with help of the theory of parameter-dependent connected components developed by us in a previous work. We may study various properties of an image at the connected components level, from the low level vision to an intermediate level vision. Using the information obtained from various component histograms and certain pre-knowledge, we describe how to select suitable values of the parameters so that an object in a gray image may be represented by a parameter-dependent component. Segmentation of the object could be conducted by locating the corresponding component. Our approach can be applied to a wide variety of images as we do not make any assumptions about the image formation model, and the method is independent of the type of the grid system used for the digitization process and the type of pixel adjacency relation.