You're reading from Mastering OpenCV 4 with Python

Product typeBook

Published inMar 2019

Reading LevelExpert

PublisherPackt

ISBN-139781789344912

Edition1st Edition

Languages

Python

Tools

OpenCV

Concepts

Computer Vision

Author (1)

Alberto Fernández Villán

Summary

In this chapter, all the main concepts related to histograms have been reviewed. In this sense, we have seen what a histogram represents and how it can be calculated by using OpenCV, NumPy, and Matplotlib functions. Additionally, we have seen the difference between grayscale and color histograms, showing how to calculate and show both types. Histogram equalization is also an important factor when working with histograms, and we have seen how to perform histogram equalization to both grayscale and color images. Finally, a histogram comparison can also be very helpful in order to perform an image comparison. We have seen the four metrics OpenCV provides to measure the similarity between two histograms.

In connection with the next chapter, the main thresholding techniques (simple thresholding, adaptive thresholding, and Otsu's thresholding, among others) will be covered...

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Mastering OpenCV 4 with Python

Published in: Mar 2019Publisher: PacktISBN-13: 9781789344912

Author (1)

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.
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