Detection of Image occurrences using a template mechanism

Introduction

• The objective is to determine the position of all instances of a given template in an parent image.
• We have used template matching mechanism to identify the template image inside the parent image.
• Template matching
  • A method for searching and finding the location of a template image in a parent image.
  • It simply slides the template image over the input image (as in 2D convolution) and compares the template and patch of input image under the template image.

Implementation Assumptions

• Given template image is in the same scale of the parent image.
• Otherwise we have to rescale the template image to the same scale of the parent image.

Implementation Process

• Step 01 - Reading Images and Templates

• Step 02 - Converting RGB images to Grayscale

• Step 03 - Creating a Mask Filter

• Step 04 - Template Matching

  • For template matching we have used openCV function matchTemplate() which requires 3 main parameters.

    • Input image
    • Template image
    • Template matching methodology

  • As the algorithm methodology we choosed normalized sum of squared differences

  

• Step 05 - Thresholding

• Step 06 - Tagging The Occurrences

• Step 07 - Combining The Mask

• Step 08 - Display the Output

ScreenShots

Used Technologies

• OpenCV using Python
• Tkinter Standard GUI Library
• Pillow Library
• Page UI building Tool

Installation Guidance

PREREQUISITES

• Python 3.7 or above
• Install Tkinter, Pillow libraries

Developers

Dinuka Kasun Medis	Michelle Karunarathne	Ravindu Sachintha	Pasindu Madusanka	Sachintha Rathnayake

Contributing

Warmly welcome to developers for contributing this Project. Make sure to open an issue and communicate with us before creating a Pull Request.

License

The PersoAd System is open-sourced software solution licensed under the GNU General Public License v3.0.