Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion. II
SIAM Journal on Numerical Analysis
Nonlinear multiscale representations for image segmentation
Computer Vision and Image Understanding
Smoothing and edge detection by time-varying coupled nonlinear diffusion equations
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Astronomical image restoration using an improved anisotropic diffusion
Pattern Recognition Letters
Information Processing Letters
An anisotropic diffusion-based defect detection for low-contrast glass substrates
Image and Vision Computing
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Behavioral analysis of anisotropic diffusion in image processing
IEEE Transactions on Image Processing
Image recovery using the anisotropic diffusion equation
IEEE Transactions on Image Processing
Anisotropic diffusion of multivalued images with applications to color filtering
IEEE Transactions on Image Processing
Forward-and-backward diffusion processes for adaptive image enhancement and denoising
IEEE Transactions on Image Processing
Local Variance-Controlled Forward-and-Backward Diffusion for Image Enhancement and Noise Reduction
IEEE Transactions on Image Processing
An improved anisotropic diffusion model for detail- and edge-preserving smoothing
Pattern Recognition Letters
On the choice of the parameters for anisotropic diffusion in image processing
Pattern Recognition
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In this paper, an anisotropic diffusion model with a generalized diffusion coefficient function is presented for defect detection in low-contrast surface images and, especially, aims at material surfaces found in liquid crystal display (LCD) manufacturing. A defect embedded in a low-contrast surface image is extremely difficult to detect, because the intensity difference between the unevenly illuminated background and the defective region is hardly observable and no clear edges are present between the defect and its surroundings. The proposed anisotropic diffusion model provides a generalized diffusion mechanism that can flexibly change the curve of the diffusion coefficient function. It adaptively carries out a smoothing process for faultless areas and performs a sharpening process for defect areas in an image. An entropy criterion is proposed as the performance measure of the diffused image and then a stochastic evolutionary computation algorithm, particle swarm optimization (PSO), is applied to automatically determine the best parameter values of the generalized diffusion coefficient function. Experimental results have shown that the proposed method can effectively and efficiently detect small defects in various low-contrast surface images.