Morphology

Mathematical morphology is a theory and technique for the analysis and processing of geometrical structures, most commonly applied to digital images. Based on set theory, it operates by probing an image with a small, predefined shape known as a structuring element to transform it. The fundamental operations of erosion (shrinking features) and dilation (expanding features), along with their combinations like opening and closing, allow for a wide range of tasks including noise removal, feature extraction, boundary detection, and skeletonization, making it a powerful tool in image processing and computer vision.

  1. Introduction to Mathematical Morphology
    1. Definition and Scope
      1. Core Concepts and Goals
        1. Structural Analysis of Images
          1. Shape-Based Processing
            1. Nonlinear Image Operations
            2. Historical Development
              1. Origins in Set Theory
                1. Contributions of Matheron and Serra
                  1. Evolution and Modern Applications
                  2. Binary vs. Grayscale Morphology
                    1. Binary Image Representation
                      1. Grayscale Image Representation
                        1. Operational Differences
                        2. Applications Overview
                          1. Image Enhancement
                            1. Feature Extraction
                              1. Segmentation
                                1. Noise Reduction