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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
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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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The Canny edge detector


Having learned about and also implemented the Sobel edge detector in the previous section, we now turn our attention to yet another edge detection algorithm, namely the Canny edge detector. It's named after its inventor John F. Canny who came up with the algorithm in 1986. The algorithm is much more involved than the Sobel edge detector and is considered to be superior to the latter.

The basic guiding principles powering the Canny detector remain the same. This means that we will still use the gradient values as indicators of whether the pixel belongs to a potential edge region or not. However, there are certain additional steps that are performed by the detector to improve the quality of detected edges. We provide a brief explanation of the same. Note that we won't be getting into the intricate mathematical details behind Canny. Rather, we would only be sharing the intuitions that motivate the additional steps that the algorithm performs. In addition to improving...

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Learning OpenCV 3 Application Development
Published in: Dec 2016Publisher: PacktISBN-13: 9781784391454

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