#
connected-component-labelling
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This repository is a collection of fundamental digital image processing operations and algorithms performed on greyscale images, or Portable Grey Map (PGM) files, using different data structures in C++, as part of an assignment and final project module for the Data Structures (CS2001) course.
Topics learned and implemented as part of Computer Vision course
Updated
Feb 16, 2019
Python
All assignments completed as a part of my Digital Image Processing Course
Updated
Dec 10, 2019
Jupyter Notebook
Code for Parallel Algorithms assignments (Fall 2019).
Practical activity #2, Data Structures, in Computer Engineering graduation.
JavaANPR: Automatic Number Plate Detection of Vehicle Images Based On Edge Detection and Morphological Approach
Updated
Mar 11, 2021
Java
Final project in Parallel Computation
Implemented parallel and distributed algorithms using OpenMP, Apache Spark and NVIDIA CUDA
A program to inspect images of o-rings for visible defects.
Updated
May 28, 2020
Python
Flow Puzzle Solver logic in CPP
Repository for my Data Structures and File Processing course at SUNY Oswego taught by Prof. Ioana Coman during the spring 2019 semester.
Matlab image processing programs without using built-in functions.
Updated
Mar 23, 2022
MATLAB
Data Structures: Arrays, Stacks, Queues, Graphs applications in image processing, tag parsing and routes/maps respectively.
Extraction of connected components from the images with PGM file format using Otsu's thresholding and BFS/DFS methods
App which solves the puzzles from the game Flow Free!
Updated
Nov 19, 2023
JavaScript
Connected Component Labelling using opencv
Connected Component Labelling
Updated
Feb 14, 2019
Jupyter Notebook
An image processing library, including methods of filtering, object detection, noise reduction, etc
A generic, STL-like and image-agnostic C++ library for connected component labelling and feature extraction.
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