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An introduction to digital image processing
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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.read more
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Proceedings ArticleDOI
Adaptative Smart-Binarization Method: For Images of Business Documents
TL;DR: This paper proposes in this paper a smart-binarization method of the images of business documents that offers a better reading of characters by the OCR and remains constant with the variation of the local window size through the use of integral images.
Journal ArticleDOI
Hybrid threshold optimization between global image and local regions in image segmentation for melasma severity assessment
Yunfeng Liang,Lei Sun,Wee Ser,Feng Lin,Evelyn Yuxin Tay,Emily Yiping Gan,Tien Guan Steven Thng,Zhiping Lin +7 more
TL;DR: In this paper, a method of hybrid threshold optimization between a given image and its local regions is proposed and used for melasma image segmentation, where an analytic optimal hybrid threshold solution is obtained by minimizing the deviation between the given image, and its segmented outcome.
Journal ArticleDOI
Super-Thresholding: Supervised Thresholding of Protein Crystal Images
TL;DR: This study proposes a novel approach called “super-thresholding” that utilizes a supervised classifier to decide an appropriate thresholding method for a specific image, and it gives the best performance for protein crystallization dataset in the authors' experiments.
Journal ArticleDOI
Text area segmentation from document images by novel adaptive thresholding and template matching using texture cues
Seba Susan,K. M. Rachna Devi +1 more
TL;DR: The proposed adaptive thresholding mimics the ability of the human eye to iteratively adjust to varying light intensities through iterative gamma correction followed by contrast stretching so that the text becomes well defined against the background clutter.
Proceedings ArticleDOI
A fast adaptive binarization method for complex scene images
TL;DR: A novel adaptive binarization method based on wavelet filter is proposed, which shows comparable performance to other similar methods and processes faster, so that it is more suitable for real-time processing and applicable for mobile devices.
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