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
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
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
Fast curvilinear structure extraction and delineation using density estimation
Computer Vision and Image Understanding
Micro-crack inspection in heterogeneously textured solar wafers using anisotropic diffusion
Image and Vision Computing
Wavelet-based defect detection in solar wafer images with inhomogeneous texture
Pattern Recognition
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In this paper, we propose an anisotropic diffusion scheme to detect defects in low-contrast surface images and, especially, aim at glass substrates used in TFT-LCDs (Thin Film Transistor-Liquid Crystal Displays). In a sensed image of glass substrate, the gray levels of defects and background are hardly distinguishable and result in a low-contrast image. Therefore, thresholding and edge detection techniques cannot be applied to detect subtle defects in the glass substrates surface. Although the traditional diffusion model can effectively smooth noise and irregularity of a faultless background in an image, it can only passively stop the diffusion process to preserve the original low-contrast gray values of defect edges. The proposed diffusion method in this paper can simultaneously carry out the smoothing and sharpening operations so that a simple thresholding can be used to segment the intensified defects in the resulting image. The method adaptively triggers the smoothing process in faultless areas to make the background uniform, and performs the sharpening process in defective areas to enhance anomalies. Experimental results from a number of glass substrate samples including backlight panels and LCD glass substrates have shown the efficacy of the proposed diffusion scheme in low-contrast surface inspection.