OpenCV

Learn to extract frequently used properties of objects like Solidity, Equivalent Diameter, Mask image, Mean Intensity. Also covers extreme points, aspect ratio, and more.

Learn to find different features of contours like area, perimeter, centroid, bounding box. We cover cv2.moments(), cv2.contourArea(), cv2.minAreaRect() and many more functions.

Learn about histogram backprojection for image segmentation and object finding. We cover cv2.calcBackProject() with both NumPy and OpenCV implementations.

Learn to find and plot 2D histograms. We will use Hue and Saturation values for color histograms with cv2.calcHist() and np.histogram2d().

Learn the concepts of histogram equalization and use it to improve the contrast of images. We cover cv2.equalizeHist() and CLAHE.

Learn to find the Fourier Transform of images using OpenCV and NumPy. We will see cv2.dft(), cv2.idft() and frequency domain applications.

Learn to use Hough Transform to find circles in an image. We will see cv2.HoughCircles() function with practical examples.

Learn to detect lines in an image using Hough Transform. We will see cv2.HoughLines() and cv2.HoughLinesP() functions with examples.

In this article we will learn simple thresholding, adaptive thresholding, and Otsu's thresholding, and we will learn these functions: cv2.threshold, cv2.adaptiveThreshold