Learning Image Processing

This repository includes my work in the journey to learn Image Processing.

the repository consists of 9 labs covering fundamental topics in Image Processing.

Lab3: Smoothing

• median filter to noisy image with S&P

• Gaussian filter with different sigma

Lab4: Contrast Enhancement

• Negative transformation

• Histogram Equalization

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Lab5: Edge Detection

• Applying Roberts and Sobel edge detectors

• Canny Edge detector with different smoothing sigma and trying different low/high thresholds
  

Lab6: Morphology

• Applying erosion and dilation to coins

• Credit Card Number Extraction: by using erosion and dilation along with contours to get bounding boxes

• Skeltonize the horse Vs thin by only 20 iteration

Lab7: Segmentation 1

• Segmenting the grass from the image by calculating the distance from grass color, then apply threshold.

  Lab8: Segmentation 2 - adaptive thresholding techniques

• histogram automatic thresholding technique result in threshold = 89.

  Lab9: textures - segmentation

• extracting glcm features from different textures then use them to identify and segment these textures in a given image like cotton, jeans, and background.