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You're reading from  Learning OpenCV 3 Application Development

Product typeBook
Published inDec 2016
Reading LevelIntermediate
PublisherPackt
ISBN-139781784391454
Edition1st Edition
Languages
C++
Tools
OpenCV
Concepts
Computer Vision
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Author (1)
Samyak Datta
Samyak Datta
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Samyak Datta

Samyak Datta has a bachelor's and a master's degree in Computer Science from the Indian Institute of Technology, Roorkee. He is a computer vision and machine learning enthusiast. His first contact with OpenCV was in 2013 when he was working on his master's thesis, and since then, there has been no looking back. He has contributed to OpenCV's GitHub repository. Over the course of his undergraduate and master's degrees, Samyak has had the opportunity to engage with both the industry and research. He worked with Google India and Media.net (Directi) as a software engineering intern, where he was involved with projects ranging from machine learning and natural language processing to computer vision. As of 2016, he is working at the Center for Visual Information Technology (CVIT) at the Indian Institute of Information Technology, Hyderabad.
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Types of simple image thresholding

The following table describes the different types of simple image thresholding operations that have been made available by the OpenCV developers:

Threshold Type

Threshold Function

THRESH_BINARY

THRESH_BINARY_INV

THRESH_TRUNC

THRESH_TOZERO

THRESH_TOZERO_INV

THRESH_OTSU

Uses the Otsu's method to compute the optimal threshold value

The flag representing the last thresholding method-Otsu's method is a little different (slightly more complicated) than the others. It relies on Image Histograms, our topic of discussion for the next chapter. For those of you who know what histograms are, the Otsu's method essentially assumes that the histogram for the image consists of two peaks-one corresponding to the background (black) and the other for the foreground (white). The computational steps in the algorithm try to come up with a threshold value that best separates the two peaks in the image histogram. We won't be discussing...

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Learning OpenCV 3 Application Development
Published in: Dec 2016Publisher: PacktISBN-13: 9781784391454
© 2016 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Samyak Datta

Samyak Datta has a bachelor's and a master's degree in Computer Science from the Indian Institute of Technology, Roorkee. He is a computer vision and machine learning enthusiast. His first contact with OpenCV was in 2013 when he was working on his master's thesis, and since then, there has been no looking back. He has contributed to OpenCV's GitHub repository. Over the course of his undergraduate and master's degrees, Samyak has had the opportunity to engage with both the industry and research. He worked with Google India and Media.net (Directi) as a software engineering intern, where he was involved with projects ranging from machine learning and natural language processing to computer vision. As of 2016, he is working at the Center for Visual Information Technology (CVIT) at the Indian Institute of Information Technology, Hyderabad.
Read more about Samyak Datta

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