README.md

VisionX: Advanced Image Processing Toolbox

VisionX is a niche desktop application crafted in C++ utilizing the Qt framework. It offers a variety of options for manipulating images,with an easy to use interface, including noise addition, filtering, edge detection, histogram analysis, image equalization and normalization, thresholding, frequency domain filters, and the creation of hybrid images making it suitable for a wide range of applications, including image processing, object detection,image features extraction, and more.

Table of contents:

• Project Features
• Project Structure Overview
• How to Run The Project
• Download Demo
• Contributors

Project Features:

1. Filters, Noise and Edge Detectors tab:
   Includes 3 types of noise that the user can add to grey/coloured images:

   Uniform Noise	Guassian Noise	Salt & Pepper Noise

   Includes 4 edge detector types with the ability to control any additional option for detector:

   Sobel	Roberts	Perwitt	Canny

   Includes 3 types of filter enabling user to control kernel size:

   Average Filter	Gaussian Filter	Median Filter

   for more details about this tab and results check Report 1

2. Normalization, Equalization and Thresholding tab:
   Shows images histogram with options to normalize or equalize:

   Histogram	Normalization	Equalization

   Apply both global or local thresholding on uploaded image:

   Local	Global

   for more details about this tab and results check Report 1

3. Frequency Domain Filters and Hybrid Image tab: User can upload an image and determine the radius for each filter type(high pass or low pass)

   High pass	Low pass

   for more details about this tab and results check Report 1

4. Hough Transform tab: This tab enbles users to apply Line/ Circle / Ellipse hough transform:

   Line	Circle	Ellipse

   for more details about this tab and results check Report 2

5. Active Contour tab: User has the ability to select cirlce from image and tune parameters to contour objects.

   Example 1	Example 2

   for more details about this tab and results check Report 2

6. Harris and Lambda Corner detector tab: User can detect corners by Harris or lambda methods and change kernel size and threshold.

   Harris	Lambda

   for more details about this tab and results check Report 3

7. Image Matching Methods tab: User can match the image template and full image with 2 methods:

   Square Sum of Differences method	Cross-Correlation Method

   for more details about this tab and results check Report 3

8. Sift Descriptors tab: User can upload one or two images to get SIFT Keypoints with options to tune, and then compute keypoints matching between images.

   

   for more details about this tab and results check Report 3

9. Advanced Thresholding tab: Includes Global Thresholding with 2 methods:

   Ostu Thresholding	Optimal Thresholding

   Includes Local Multi-level Thresholding and Global Multi-level Thresholding:

   Local Multi-level Thresholding	Global Multi-level Thresholding

   for more details about this tab and results check Report 4

10. Segmentation Methods tab: User can segment RGB images with 4 types of segmentation:

    K-Means Segmentation	Mean Shift Segmentation

    Agglomerative Segmentation	Region Growing

for more details about this tab and results check Report 4

Project Structure Overview:

main
├─ Models : header/source files related to CV algorithms implementation.
├─ docs : reports related to results and theory behind.
├─ Gallery : images used for testing.
├─ Controllers: Contains the controllers responsible for handling communication between models and views.
├─ UI : include ui/header / resource file related to pages design.
└─ Helpers: used for common app logic and different ui functionality.

Getting Started

Dependenices

- Qt Version 6.4.2
- OpenCV 4.9.0

Installation

1. Ensure Qt is installed on your system.
2. Clone the VisionX repository to your local machine.

How to run the project

• Download and Install Qt from the online installer using minGW 64 architecture.

www.qt.io

• Download and build openCV 4.9.0 from their website

www.opencv.org/releases/

• if you don't know how to build OpenCV on your PC please refer to the installCV.md

• Go to the Task1.pro file and ensure that openCV libraries are referred to in your pc like that.

Windows

INCLUDEPATH += <yourCV build folder path>\install\include

LIBS += -L<yourCV build folder path>\release\lib \
    -lopencv_calib3d490                 \
    -lopencv_core490                    \
    -lopencv_features2d490              \
    -lopencv_flann490                   \
    -lopencv_highgui490                 \
    -lopencv_imgproc490                 \
    -lopencv_imgcodecs490               \
    -lopencv_photo490                   \
    -lopencv_stitching490               \
    -lopencv_ts490                      \
    -lopencv_video490                   \
    -lopencv_videoio490                 \
    -lopencv_objdetect490               \

Linux

CONFIG += link_pkgconfig
PKGCONFIG += opencv4

Building

1. Open the project in Qt Creator.
2. Make sure your .pro file matches commonpro.txt file
3. Build the project to generate the executable.

Usage

1. Launch the application.
2. Open an image file.
3. Select desired operations from the menu.
4. Adjust parameters as needed.
5. View & analyze the processed image.

Download Demo

Contributors

Abdulrahman Emad

Mourad Magdy

Ziad Meligy

Mariam Ahmed

Youssef Ashraf