Image Processing in Python
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Chapter-1: Introducing Image Processing and scikit-image
Jump into digital image structures and learn to process them! Extract data, transform and analyze images using NumPy and Scikit-image. Convert RGB images to grayscale, get data from them, obtain histograms containing very useful information, and separate objects from the background!
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Chapter-2: Filters, Contrast, Transformation and Morphology
Detect object shapes using edge detection filters, improve medical images with contrast enhancement and even enlarge pictures to five times its original size! Apply morphology to make thresholding more accurate when segmenting images and go to the next level of processing images with Python.
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Chapter-3: Image restoration, Noise, Segmentation and Contours
Apply image restoration to remove objects, logos, text, or damaged areas in pictures! Also learn how to apply noise, use segmentation to speed up processing, and find elements in images by their contours.
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Chapter-4: Advanced Operations, Detecting Faces and Features
Have a deeper knowledge of image processing by being able to detect edges, corners, and even faces! Learn how to detect not just front faces but also face profiles, cat, or dogs. Apply the skills to more complex real-world applications. Learn to master several widely used image processing techniques with very few lines of code!