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You're reading from  Mastering OpenCV 4 with Python

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Published inMar 2019
Reading LevelExpert
PublisherPackt
ISBN-139781789344912
Edition1st Edition
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Alberto Fernández Villán
Alberto Fernández Villán
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Alberto Fernández Villán

Alberto Fernndez Villn is a software engineer with more than 12 years of experience in developing innovative solutions. In the last couple of years, he has been working in various projects related to monitoring systems for industrial plants, applying both Internet of Things (IoT) and big data technologies. He has a Ph.D. in computer vision (2017), a deep learning certification (2018), and several publications in connection with computer vision and machine learning in journals such as Machine Vision and Applications, IEEE Transactions on Industrial Informatics, Sensors, IEEE Transactions on Industry Applications, IEEE Latin America Transactions, and more. As of 2013, he is a registered and active user (albertofernandez) on the Q&A OpenCV forum.
Read more about Alberto Fernández Villán

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Compressing contours

Detected contours can be compressed to reduce the number of points. In this sense, OpenCV provides several methods to reduce the number of points. This can be set with the parameter method. Additionally, this compression can be disabled by setting the flag to cv2.CHAIN_APPROX_NONE, where all boundary points are stored; hence, no compression is performed.

The cv2.CHAIN_APPROX_SIMPLE method can be used to compress the detected contours because it compresses horizontal, vertical, and diagonal segments of the contour, preserving only endpoints. For example, if we use cv2.CHAIN_APPROX_SIMPLE to compress the contour of a rectangle, it will only be composed of four points.

Finally, OpenCV provides two more flags for compressing contours based on the Teh-Chin algorithm, which is a non-parametric method. The first step of this algorithm determines the region of support...

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Mastering OpenCV 4 with Python
Published in: Mar 2019Publisher: PacktISBN-13: 9781789344912

Author (1)

author image
Alberto Fernández Villán

Alberto Fernndez Villn is a software engineer with more than 12 years of experience in developing innovative solutions. In the last couple of years, he has been working in various projects related to monitoring systems for industrial plants, applying both Internet of Things (IoT) and big data technologies. He has a Ph.D. in computer vision (2017), a deep learning certification (2018), and several publications in connection with computer vision and machine learning in journals such as Machine Vision and Applications, IEEE Transactions on Industrial Informatics, Sensors, IEEE Transactions on Industry Applications, IEEE Latin America Transactions, and more. As of 2013, he is a registered and active user (albertofernandez) on the Q&A OpenCV forum.
Read more about Alberto Fernández Villán