A note on the gradient of a multi-image
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward a Symbolic Representation of Intensity Changes in Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Authenticating Edges Produced by Zero-Crossing Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image understanding research at Carnegie Mellon
Proceedings of a workshop on Image understanding workshop
Edge detection in multispectral images
CVGIP: Graphical Models and Image Processing
Edge, Junction, and Corner Detection Using Color Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge and Corner Detection by Photometric Quasi-Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting boundaries in a vector field
IEEE Transactions on Signal Processing
On the detection of edges in vector images
IEEE Transactions on Image Processing
Robust photometric invariant features from the color tensor
IEEE Transactions on Image Processing
A morphological gradient approach to color edge detection
IEEE Transactions on Image Processing
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Most conventional derivative-based color edge detectors have shortcomings such as high computational cost, difficulty in implementation and missing edges. In this paper, we propose a new, simple and effective cubical voxels and virtual electric field model (CVVEFM) for edge detection in color images. The main idea is to model a color image as the network of elementary cubical points (voxels) of virtual electric charges. These charges are uniformly distributed on a cube, in electrostatic balance. In this edge detector, three designed operators which provide approximate gradients of each plane color component are determined. The method is based on the combinations of simple cubical voxels (CV) and virtual electric field (VEF) models. The CV model describes the color pixels as cubical voxels. The VEF model describes the voxels as punctual electric charges by mathematical expressions. Both are used simultaneously to describe the color images including more edges than usually used. Fast, easy to implement and satisfactory edge detection due to its characteristics is accomplished with the CVVEFM. Some color images illustrate the results.