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.
- 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.
- Input Images: Provide paths to two images that you want to compare.
- Run the Script: Execute the script to compute the similarity between the provided images.
- View Results: The script will output a similarity value indicating the degree of similarity between the images.
- Python 3.x
- Required Python libraries: numpy, scikit-fuzzy, Pillow
- Clone or download this repository.
- 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!