raman0330/image-similarity-check-using-fuzzy-system

Image Similarity Comparison with Fuzzy Logic

Overview

This project implements a fuzzy logic-based approach to comparing images. It provides a flexible framework for assessing the similarity between two images, considering various features such as intensity difference and edge similarity.

Features

• Fuzzy Logic-Based Comparison: Utilizes fuzzy logic to handle the inherent uncertainty and imprecision in image comparison tasks.
• Customizable Input Variables: Allows users to define input variables relevant to image comparison, such as intensity difference and edge similarity.
• Flexible Rule-based System: Enables users to define rules that determine the overall similarity between images based on the combination of input variables.
• Context-Aware Design: While the provided example focuses on intensity difference and edge similarity, the framework can be extended to incorporate other features based on specific requirements.
• Usage Scenarios: Suitable for a variety of applications including content-based image retrieval, duplicate image detection, and quality assessment in image processing.

Usage

1. Input Images: Provide paths to two images that you want to compare.
2. Run the Script: Execute the script to compute the similarity between the provided images.
3. View Results: The script will output a similarity value indicating the degree of similarity between the images.

Requirements

• Python 3.x
• Required Python libraries: numpy, scikit-fuzzy, Pillow

Installation

1. Clone or download this repository.
2. Install the required Python libraries using pip:

   pip install numpy scikit-fuzzy Pillow
   

Feel free to further customize it according to your project's specific details and requirements!