Computer Vision

original non quantized

Reduce the number of Colors of an image using Uniform Quantization

Reducing the number of colors in an image is also called Color quantization. It’s commonly used for generating GIF images which currently supports only 256 colors. The general idea is, group similar colors in an image into regions, replace them with the color which closely resembles or represents the region. This color is also called …

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Basics of Image Convolution

Convolution is a process used for applying general-purpose filter effects like blurring, sharpening, embossing, edge detection, and more. To understand convolutions we must first understand what a convolution matrix is, also referred to as kernel. Take for example the blurring filter. In blur filter, we set each pixel to the mean of its neighbouring pixels. …

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Segmenting lines in handwritten documents using A* Path planning algorithm

In this article, I will explain a widely used method for segmenting handwritten documents into individual lines. Below is a sample output from my algorithm. The below flowchart outlines the different steps involved in the segmentation process. The explained method will only work with non-skewed documents. To de-skew the document, you can refer to my …

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Converting Color Images to Grayscale using numpy and some Mathematics

An extremely magnified image at the end is just blocks of colors called pixels, where each pixel is formed by the combination of Red, Blue and Green, our primary colors. RGB color space or RGB color system, constructs all the colors from the combination of the intensities of Red, Green and Blue colors. The red, green and …

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