Image Processing (imgproc module)

Table of Contents

• • • • Basic
      • Transformations
      • Histograms
      • Contours
      • Others

The imgproc module in OpenCV is a collection of per-pixel image operations (color conversions, filters) drawing (contours, objects, text), and geometry transformations (warping, resize) useful for computer vision. Here's an overview of the content in the imgproc module, categorized for easier navigation:

Basic

These tutorials cover fundamental image processing tasks, such as drawing on images, applying filters, and morphological operations.

• Basic Drawing
• Random generator and text with OpenCV
• Smoothing Images
• Eroding and Dilating
• More Morphology Transformations
• Hit-or-Miss
• Extract horizontal and vertical lines by using morphological operations
• Image Pyramids
• Basic Thresholding Operations
• Thresholding Operations using inRange

Transformations

These tutorials explore more advanced transformations that modify the image in various ways, such as filtering, warping, and edge detection.

• Making your own linear filters!
• Adding borders to your images
• Sobel Derivatives
• Laplace Operator
• Canny Edge Detector
• Hough Line Transform
• Hough Circle Transform
• Object detection with Generalized Ballard and Guil Hough Transform
• Remapping
• Affine Transformations

Histograms

Histograms are vital for image analysis, and these tutorials cover operations like equalization, comparison, and back projection.

• Histogram Equalization
• Histogram Calculation
• Histogram Comparison
• Back Projection
• Template Matching

Contours

Contours are curves that represent the boundaries of objects in an image. These tutorials cover techniques to detect and analyze contours.

• Finding contours in your image
• Convex Hull
• Creating Bounding boxes and circles for contours
• Creating Bounding rotated boxes and ellipses for contours
• Image Moments
• Point Polygon Test

Others

These tutorials cover specialized image processing techniques for more complex tasks like deblurring, noise removal, and image segmentation.

• Image Segmentation with Distance Transform and Watershed Algorithm
• Out-of-focus Deblur Filter
• Motion Deblur Filter
• Anisotropic image segmentation by a gradient structure tensor
• Periodic Noise Removing Filter