Skip to content

This repository contains the implementation of an Object Detection and Classification & Line and Circle Detection Application

License

Notifications You must be signed in to change notification settings

OluwaseunOjeleye/Image-Processing-App

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Image Processing App

This project consist of the implementation of image processing projects without the use of any image processing library (such as opencv). It was implemented with ​Qt development software on a Linux platform and the used language is C++. The projects implemented so far are:

  1. Object Detection and Classification based on Geometric Invariant Moment.
  2. Line and Circle detection based on Hough Transform.

App

Project 1: Object Detection and Classification based on Geometric Invariant Moment

This project consist of the implementation of objects detection and classification program which detects and classifies objects (such as rice, beans, etc.) based on their geometric shape. The processes that are implemented in this project are:

  • Noise Elimination
    • Mean Filtering
  • Image Segmentation
    • OTSU Thresholding
    • K-Means Cluster Binary Thresholding
  • Morphological Image Processing
    • Dilation
    • Erosion
    • Opening
    • Closing
    • Boundary Extraction
  • Labeling and Bounding
    • Connected-component Analysis (CCA)
    • Drawing Bound Boxes
  • RST-invariant moment-based feature extraction and feature analysis
  • Distance based supervised learning for image classification

The diagram below shows a typical image processing system and the sub-processes involved in this project:

Object Detection and Classification

Project 2: Line and Circle detection based on Hough Transform

This project consist of the implementation of lines and circles detection program using Hough Transform. This project is the extension of the Object detecting and classifying application’s components. The processes that are implemented in this project are:

  • Smoothing
    • Gaussian Blur(Gaussian Smoothing)
  • Edge Detection
    • Sobel Edge Detection
    • Canny Edge Detection
      • Non-maximum Suppression
      • Hysteresis thresholding
  • Hough Line Transform
  • Hough Circle Transform

The diagram below shows the sub-processes involved in this project:

Line and Circle Detection

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Linux Machine with QT5 Creator.

Downloading

Cloning The GitHub Repository

git clone https://github.com/OluwaseunOjeleye/Objects-Detection-and-Classification---Line-and-Circle-Detection-App.git

How to use the program

Once you've cloned the repository, instructions on how to use the application can be found in Report.pdf

Author

  • Jamiu Oluwaseun Ojeleye