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Dec 06, 2013 · OpenCV Introduction 1. (Open Source Computer Vision) 2. Outline Overview and practical issues. A selection of OpenCV functionality: – – Object classification and tracking – Image enhancement Face detection and recognition Conclusion and further resources.

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I had used this tutorial in guiding me in developing an OpenCV app using Java on Android Studio that would be able to process frames for object recognition. As I have finished, I have encountered an error; the dreaded NullPointerException us Java programmers face.

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Lately, I have been involved in developing applications/libraries in C++ @ my work place. So, I thought if I start working on open source IP-APIs like OpenCV, it will help my coding skills in C++. I promise you, I will regularly update this blog with what I study/learn in openCV and Image Processing.

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Limitation in the Face Detection. The Facial Recognition System is essential nowadays, and it has come a long way. Its use is essential in quite some applications, for example - Photo retrieval, surveillance, authentication/access, control systems etc.

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Goal Test OpenCV histogram. OpenCV_Histogram.java import java.awt.EventQueue; import javax.swing.ImageIcon; import...

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In this chapter learn how to enhance the contrast of an image using histogram equalization. We use the OpenCV function equalizeHist() method. It can be found under Imgproc package. Its syntax is given below − Imgproc.equalizeHist(source, destination); The parameters are described below −

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