Howto

💡 Problem Formulation: In the realm of computer vision and image processing, there are situations where combining two images becomes necessary. Specifically, the bitwise OR operation allows for the merging of two images, pixel by pixel, such that each bit is set to 1 if either pixel’s corresponding bit is 1. For instance, when overlaying … Read more

💡 Problem Formulation: Drawing polylines on images is a common task in image processing that can be used for annotating, geometric transformations, or creating masks. The challenge is to draw a series of connected lines – or a polyline – on the given image accurately, and OpenCV provides the functionality in Python to achieve this. … Read more

💡 Problem Formulation: Detecting edges and gradients in images is a foundational task in computer vision that allows for feature extraction and object boundary detection. In this article, we aim to effectively find image gradients by applying Sobel and Laplacian derivatives using the OpenCV library in Python. The input is a digital image, and the … Read more

💡 Problem Formulation: Computing the morphological gradient of an image can highlight its edges by subtracting the eroded image from the dilated image. Users leverage this for applications like edge detection, image segmentation, and shape analysis. Input is a grayscale image, and desired output is an image that represents the gradient magnitude. Method 1: Basic … Read more

💡 Problem Formulation: When working with image processing, a common task is to apply custom filters to enhance or extract features from images. Convolution is a mathematical operation used to apply these filters. Suppose we have an image and we want to highlight edges, blur, sharpen, or detect specific patterns using a custom designed filter. … Read more

💡 Problem Formulation: You have an image with a planar object, and you want to adjust its perspective to simulate a different viewpoint. For example, you’ve photographed a painting that wasn’t perfectly frontal and want to rectify it to appear as if viewed head-on. We plan to cover methods to apply perspective transformations using Python’s … Read more

💡 Problem Formulation: Converting a colored image to HLS (Hue, Lightness, Saturation) is often necessary for image processing tasks such as object tracking, computer vision, and image analysis. For example, given an input image in BGR (Blue, Green, Red) format, the task is to transform this image to HLS format using OpenCV in Python to … Read more

💡 Problem Formulation: You have an image and need to annotate it by drawing an arrowed line to highlight specific areas or to point to something. In OpenCV Python, this can be done through various methods. Imagine you have an image representing a map, and you want to draw an arrow from one city to … Read more

💡 Problem Formulation: In image processing, it’s often necessary to identify and encapsulate contours within bounding rectangles. OpenCV Python offers several methods to accomplish this. Given a binary or edge-detected image, we want to locate contours and create bounding boxes around them to extract or analyze these isolated regions. Method 1: Using cv2.boundingRect() OpenCV’s cv2.boundingRect() … Read more

💡 Problem Formulation: Affine transformation in image processing refers to altering an image to correct for distortions or to apply certain effects. When using OpenCV in Python, developers often need to apply affine transformations to shift, scale, rotate or skew images. This article walks through five methods to do this on an input image, aiming … Read more

💡 Problem Formulation: The task involves performing a bitwise XOR operation on two image matrices using OpenCV in Python. Given two images of identical dimensions, the desired output is a third image where each pixel is the result of a bitwise XOR operation between the corresponding pixels of the original images. This can be useful … Read more

💡 Problem Formulation: In the realm of image processing, performing a bitwise AND operation on two images is a fundamental technique. This process involves overlaying two images on top of one another and then performing the AND operation on every corresponding pair of pixels. The result is a new image in which only the pixels … Read more