A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of digital image processing
Fundamentals of digital image processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Signal Processing: A Computer-Based Approach
Digital Signal Processing: A Computer-Based Approach
Gabor Analysis and Algorithms: Theory and Applications
Gabor Analysis and Algorithms: Theory and Applications
Computer and Robot Vision
Fundamental Frequency Gabor Filters for Object Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Optimal Gabor filters for texture segmentation
IEEE Transactions on Image Processing
The generalized Gabor transform
IEEE Transactions on Image Processing
An enhanced memetic differential evolution in filter design for defect detection in paper production
Evolutionary Computation
A Proposed Biologically Inspired Model for Object Recognition
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
Identifying a critical threat to privacy through automatic image classification
Proceedings of the first ACM conference on Data and application security and privacy
A suitable neural network to detect textile defects
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
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Gabor filter is a widely used feature extraction method, especially in image texture analysis. The selection of optimal filter parameters is usually problematic and unclear. This study analyzes the filter design essentials and proposes two different methods to segment the Gabor filtered multi-channel images. The first method integrates Gabor filters with labeling algorithm for edge detection and object segmentation. The second method uses the K-means clustering with simulated annealing for image segmentation of a stack of Gabor filtered multi-channel images. Various experiments with real images demonstrate the effectiveness of these approaches.