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Proceedings of the International MultiConference of Engineers and Computer Scientists 2017 Vol I, IME CS 2017, March 15 17, 2017, Hong Mongoose Removal and Finalization of Scanned Document Images
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How to fill out noise removal and binarization

01
Step 1: Open the image or document that you want to apply noise removal and binarization to.
02
Step 2: Use a noise removal tool or software to reduce or eliminate the noise in the image. This can be done by adjusting the settings or applying filters specifically designed for noise reduction.
03
Step 3: Once the noise is reduced, proceed to perform binarization on the image. Binarization converts the image into a black and white format, where only two colors are present: black and white.
04
Step 4: Apply a binarization algorithm or tool to achieve the desired result. This can involve adjusting the threshold level or using adaptive binarization methods.
05
Step 5: Check the output and make any necessary adjustments to fine-tune the noise removal and binarization effect.
06
Step 6: Save the processed image or document in the desired format for future use.

Who needs noise removal and binarization?

01
Graphic designers and photographers often need noise removal and binarization techniques to enhance the quality and clarity of their images.
02
Document scanners and OCR (Optical Character Recognition) software rely on noise removal and binarization to improve the accuracy of text extraction from scanned documents.
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Researchers and scientists working with image analysis and computer vision may require noise removal and binarization to improve the accuracy of their algorithms and models.
04
Artists and illustrators can utilize noise removal and binarization to create stylized or simplified versions of their artworks.
05
Individuals who want to clean up old or damaged photographs can benefit from noise removal and binarization techniques to restore and enhance the visual quality of the images.
06
Printers and publishers often apply noise removal and binarization to optimize the printing process and ensure high-quality reproductions of text and images.
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Noise removal is the process of eliminating unwanted elements from a signal. Binarization is the process of converting data into binary form, typically to create a black and white image.
Individuals or companies working with digital images or signals may be required to perform noise removal and binarization.
Noise removal and binarization can be done using software tools designed for image processing.
The purpose of noise removal and binarization is to improve the quality and clarity of images or signals.
Information on the process used, parameters selected, and the results obtained from noise removal and binarization must be reported.
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