Multi-threaded Image Processing

This project demonstrates multi-threaded image processing using both Python and Java. The goal is to implement various image filters and techniques to process images efficiently by utilizing threading to improve performance.

Project Structure

The project is divided into two main components:

• Java Image Processing:

  • Implements multiple filters, including Sobel, Gaussian, and Sepia.
  • Utilizes Java's threading capabilities to enhance performance in an interactive GUI application.

• Python Image Processing:

  • Focuses on implementing Sobel edge detection and thresholding.
  • Employs Python’s threading to handle image processing in chunks.

Features

• Multi-threaded Implementation: Both Java and Python implementations use multi-threading to process images faster by dividing the workload across multiple threads.
• Multiple Filters: The Java component includes various filters such as:
• Sobel Filter: Detects edges in images.
• Gaussian Filter: Applies Gaussian blur to images.
• Sepia Filter: Applies a warm tone effect to images.
• Sobel Edge Detection: The Python component focuses on the Sobel operator for edge detection, showcasing its application in image processing.

results

• Initial image:
  • 
• Sobel Edge Detection:
  • 
• Gaussian Filter
  • 
• Sepia Filter
  •