Implementation of the paper "Topological Structural Analysis of Digitized Binary Images by Border Following" using C language
https://github.com/RaphaelJ/friday/blob/master/src/Vision/Image/Contour.hs https://github.com/lagadic/visp/blob/master/modules/imgproc/src/vpContours.cpp https://github.com/lagadic/visp/blob/master/modules/imgproc/include/visp3/imgproc/vpContours.h https://github.com/JuliaImages/juliaimages.github.io/blob/source/docs/examples/contours/contour_detection.jl
I was able to implemet the algorithm upto the point where it can detect a contour in a test image and assign a label to it. However there is a bug which results in running the same contour detection algorithm several times for a contour detected prevoisly. I was not able to find the reason for that.
| Folder Name | What is inside |
|---|---|
| MVbR2TG | Implementaion of the paper in pure C language using Visual Studio 2019 |
| MVbR2TGavr | Implementaion of the paper to run in an AVR microcontroller. This was not successful due to the very limited storage and the processing power of the AVR (Atmel ATMEGA32A), uint8_t branch consists of an alternate approach which ues uint8_t data type instead of int type. |
| MVbR2TGpy | Includes random python scripts to 1. Generate test images and saves them in header files 2. Measure time it takes to run the findcontour function in OpenCV inorder to compare it with my algorithm 3. Visualize the processed images by the first algorithm (MVbR2TG) |
title = {Topological structural analysis of digitized binary images by border following},
journal = {Computer Vision, Graphics, and Image Processing},
volume = {30},
number = {1},
pages = {32-46},
year = {1985},
issn = {0734-189X},
doi = {https://doi.org/10.1016/0734-189X(85)90016-7},
url = {https://www.sciencedirect.com/science/article/pii/0734189X85900167},
author = {Satoshi Suzuki and KeiichiA be},
abstract = {Two border following algorithms are proposed for the topological analysis of digitized binary images. The first one determines the surroundness relations among the borders of a binary image. Since the outer borders and the hole borders have a one-to-one correspondence to the connected components of 1-pixels and to the holes, respectively, the proposed algorithm yields a representation of a binary image, from which one can extract some sort of features without reconstructing the image. The second algorithm, which is a modified version of the first, follows only the outermost borders (i.e., the outer borders which are not surrounded by holes). These algorithms can be effectively used in component counting, shrinking, and topological structural analysis of binary images, when a sequential digital computer is used.}
}