Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Segmentation of edges into lines and arcs
Image and Vision Computing
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
Digital Image Processing
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Structuring Elements for the Morphological Pattern Restoration of Binary Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Programming for Feature Discovery and Image Discrimination
Proceedings of the 5th International Conference on Genetic Algorithms
General schema theory for genetic programming with subtree-swapping crossover: part I
Evolutionary Computation
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Computer
Morphological algorithm design for binary images using genetic programming
Genetic Programming and Evolvable Machines
Genetic programming for image analysis
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
A novel evolutionary approach to image enhancement filter design: method and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An efficient image pattern recognition system using an evolutionary search strategy
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
On two approaches to image processing algorithm design for binary images using GP
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
A novel genetic programming based morphological image analysis algorithm
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Gray-scale image enhancement as an automatic process driven by evolution
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image enhancement and denoising by complex diffusion processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image enhancement via adaptive unsharp masking
IEEE Transactions on Image Processing
Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
In this paper, we propose a genetic programming algorithm to design the morphological image enhancement procedure. Given a group of morphological operations and logical operations as function set, this algorithm evolves to produce a rational procedure which can enhance the input images. A novel mechanism which combines the ground truth method and feature significance is brought forward to evaluate the performance of images enhanced by generated procedures. In each generation, the best fitted individuals are selected on the basis of fitness values, and some individuals participate in crossover or mutation with a probability. After each generation, this algorithm outputs the best individual. Seven morphological operations and five logical operations are used in this algorithm. Furthermore, the structuring elements of morphological operations are randomly generated and varied in the whole pattern space. These methods promote the expressive ability of generated procedures. Examined by the binary image feature extraction, the procedure generated by this algorithm is more accurate and intelligible than previous work. In the task of gray scale image enhancement, the generated procedure is applied to infrared finger vein images to enhance the region of interest. More accurate features are extracted and the accuracy of authentication is promoted.