IPV1 - Image Processing and Vision

Covered the fundamentals of image restoration, segmentation and denoising using MATLAB tools.


5
  • Detecting green apples
  • Detecting red apples
  • Enhance image
  • Restoration deblur
  • Restoration defob dehaze

About this project

This project explored core concepts in image processing and computer vision using MATLAB. The focus was on practical applications such as image restoration, segmentation, and denoising.

Key Features

  • Implemented k-means clustering algorithms to segment images of apples by color.
  • Enhanced images with low dynamic range or poor lighting conditions.
  • Applied dehazing, deblurring, and denoising techniques using standard MATLAB functions.
  • Evaluated and compared the effectiveness of different restoration and enhancement methods.

Challenges

  • Achieving accurate segmentation of apples with similar colors or overlapping regions.
  • Restoring image quality in cases of severe noise or blur.
  • Fine-tuning algorithm parameters for optimal results across diverse image sets.

Learnings

  • Gained hands-on experience with MATLAB’s image processing toolbox.
  • Developed an understanding of clustering algorithms for image segmentation.
  • Learned to apply and assess various restoration and enhancement techniques in real-world scenarios.
  • Improved problem-solving skills in handling challenging image datasets.
Image Processing MATLAB