Hough Transform

Hough transform is commonly used for detecting regular curves such as lines, circles, ellipses, etc. It is a technique that requires that the features we want to find, can be specified in a parametric form (e.g. by using a gemotrical equation). Hough transform is useful for computing a global descriptionm of a feature(s), where the number of classes is known in advance, by taking into consideration the local measurements that can be affected from noise.

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Edge Detection and Contour Extraction

Contour Extracion is a common image processing technique aims at indentifying the structural outline of objects in image. A contour can help in indentifying a shape of object and for such a reason, they are widely use for segmentation, text recognition, shape recognition, etc. A contour is a curved line representing the boundary of the same values or the same intensities. Before going deeper into the contour world, we have to understand the difference between edges and contours.

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Image Filtering

Filtering is perhaps the most fundamental operation of image processing and computer vision. It is a fundamental step when you have to deal with tasks like: noise reduction, contour extraction, text recognition, etc. The main filters can be divided in two big categories: low-pass filters (LPF), which help in removing noise, blurring images, etc., and high-pass filters (HPF) that help in finding edges in images. In this post, we are going to talk about: Gaussian Filter, Median Filter, and Bilater Filter and we will see some code example as well as the results of each filter applied to our lena image.

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