Mathematical Morphology Toolbox

Mathematical morphology serves as a crucial branch in the field of image processing, providing a powerful toolkit based on set theory. This toolbox, developed by international contributors, encompasses a complete ecosystem of morphological processing algorithms, delivering comprehensive coverage from fundamental to advanced operations. The toolbox's core value lies in its algorithmic completeness—it not only includes classic fundamental operations like opening (eliminating fine noise while preserving main shapes) and closing (filling small holes and smoothing contours), but also integrates advanced functionalities such as morphological reconstruction. The reconstruction algorithm employs iterative processing of marker images and masks to effectively address shape distortion issues caused by traditional morphological operations, proving particularly vital in medical image analysis and similar domains. Developers adopted a modular architecture design where each morphological operator undergoes rigorous mathematical validation, ensuring that basic operators like erosion and dilation can serve as building blocks for more complex algorithms. The toolbox specifically optimizes configurability of structural elements, supporting circular, rectangular, and even custom-shaped elements to meet neighborhood processing requirements across different scenarios. For researchers working with binary or grayscale images, the toolbox provides unified API interfaces, enabling specialized operations like top-hat transformations (extracting fine bright regions) or granulometry to be implemented through concise function calls. This design preserves academic precision while maintaining engineering practicality for applied implementations. The implementation typically involves functions like imopen() and imclose() for basic operations, while reconstruction algorithms might use imreconstruct() with marker-mask pairs for advanced processing. Structural elements can be created using strel() function with configurable shapes and dimensions.