Review of Hough and Watershed Transform Algorithms

Seminar paper from the year 2017 in the subject Computer Science - Theory, Universidad Nacional de Colombia (Engineering Faculty), course: Artificial Intelligence Techniques, language: English, abstract: Patterns isolation is one of the bases of image processing and artificial intelligence algorithms as it is the key for image segmentation and posterior classification of objects. A brief review is performed in this document, regarding the Hough and watershed transforms algorithms, and in regards to its robustness to some conditions and implementations. Recognition and isolation of patterns is a very important part of image processing and machine vision, it conforms the base to make a proper segmentation. Hough transformation is an algorithm used to determine parametric features in images and isolate them, whilst the watershed transform is an useful tool to isolate regions in images; both algorithms are commonly used in image segmentation. Throughout this document, the reader will find the Hough transform section in which a brief explanation of the Hough transform basic algorithm is presented, as well as some examples and the proposal to plot the accumulator space in polar coordinates as it might be useful for some applications, the Watershed transform section where the algorithm is explained briefly and some examples are given, the conclusions and discussion and lastly, the references, in case the reader would like to deepen in any subject.