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An introduction to digital image processing

Wayne Niblack
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The article was published on 1986-01-01 and is currently open access. It has received 1745 citations till now. The article focuses on the topics: Digital image processing & Image processing.

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Proceedings ArticleDOI

Adaptive Thresholding: A comparative study

TL;DR: A comparative study on adaptive thresholding techniques to choose the accurate method for binarizing an image based on the contrast, texture, resolution etc. of an image.
Journal ArticleDOI

Finger-vein biometric identification using convolutional neural network

TL;DR: In this article, a CNN with fused convolutional sub-sampling architecture was proposed for finger-vein recognition, which achieved an accuracy of 99.38% with an error ratio of 80/20 percent for separation of training and test samples.
Journal ArticleDOI

Color image histogram equalization by absolute discounting back-off

TL;DR: A novel color image histogram equalization approach is proposed that exploits the correlation between color components and it is enhanced by a multi-level smoothing technique borrowed from statistical language engineering in order to eliminate the gamut problem.
Journal ArticleDOI

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding.

TL;DR: A less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding is proposed.
Journal ArticleDOI

Contrast adaptive binarization of low quality document images

TL;DR: An improved method for binarizing document images by adaptively exploiting the local image contrast is proposed, which aims to overcome the common problems encountered in low quality images, such as uneven illumination, low contrast, and random noise.
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