The example recreates the VideoCapture sample from the OpenCV documentation. It uses the Imgproc module to convert the color image into single channel greyscale, apply a blur filter, and find the edges.

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The example converts a PImage (ARGB) to a Mat (BGR). It then randomly samples a pixel to compare their color values in the two formats. In order to transfer the integer array pixels[] from the PImage to the byte array of the CV_8UC4 matrix, it makes use of the ByteBuffer and IntBuffer.
 
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This example compares the pixel information between a Processing PImage and OpenCV Mat of the same external image file. The dimension of the image in Processing is width x height (x, y) while for OpenCV, it is rows() x cols() (y, x). A random point is picked and its pixel color is shown both in Processing PImage and OpenCV Mat.
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To perform the same image loading task in OpenCV, we use the imread() function in the Imgcodecs module. The function was in the Highgui module before. The image loaded in the Mat data structure is in BGR format. We shall use the split and merge commands to align the proper channels. Finally, we use a byte array to transfer the pixels information to the pixels[] array of a PImage object.
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Now we proceed to first core part of the tutorials, representation of image in Processing and OpenCV. In Processing, the class is PImage. Digital video, Movie and live webcam feed, Capture are also PImage. When we import the external image file from the data folder through loadImage(), the format will usually be RGB. The internal representation is, however, ARGB.
 
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This example will demonstrate the use of the Rect class in OpenCV and compare it with the Rectangle class in Java. The Rect class will be useful when we work on the face detection example later. The detected faces will be returned as rectangles.
 
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The Java binding of OpenCV has a number of data classes in the form of MatOfxxx, where xxx is other datatype such as Int, Float, Point. This example will demonstrate the use of MatOfInt class. These classes will usually be used for parameters passing between different OpenCV functions. We can manipulate it similar to array and List.
 
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This example will demonstrate the use of CvType, Size and Scalar.

CvType defines all the matrix types in OpenCV. It describes the number of channels, and depth information for each element (pixel) in the matrix. This example will use CV_8UC1 – 8 bits unsigned char, 1 channel. To communicate with Processing, we usually take CV_8UC4 for ARGB as the RGB format in PImage also uses 4 bytes for storage.
 
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