# Readme

The pymorph Morphology Toolbox for Python is a software for Image Analysis and Signal Processing. It is composed by a family of discrete non linear filters based on lattice operations. These filters, called morphological operators, are quite useful for restoration, segmentation and quantitative analysis of Images and Signals.

The pymorph Morphology Toolbox contains state-of-the-art morphological operators, implemented by simple algorithms. The available operators go from the classical morphological filters, used for restoration and shape description, to the modern connected filters and watersheds, so powerful for image segmentation.

The potential of the pymorph Morphology Toolbox is illustrated by several demos, that show the morphological solution of many real-life image processing problems. Some of the application areas covered are machine vision, medical imaging, desktop publishing, document processing, food industry and agriculture.

The reference manual has a page of documentation for each function of the toolbox. These pages present the respective command syntax, a detailed explanation of the necessary parameters, a short description, an application example and the formal definition.

The pymorph Morphology Toolbox deals with gray-scale and binary images (or signals) and is data type oriented. Thus, most operators perform both gray-scale and binary image (or signal) processing and the choice of the appropriate (binary or gray-scale) algorithm is automatic.

The images (or signals) may be represented by the formats: binary, 8-bit gray-scale and 16-bit gray-scale, where each pixel is represented, respectively, by a logical uint8, a uint8 and uint16 data type.

Morphological operators may be written hierarchically from two elementary operators, called dilation and erosion. pymorph Morphology Toolbox has simple implementations for dilation and erosion and permits the realization of any morphological operator by this constructive approach.

Dilations and erosions are parameterized by particular images (or signals), called structuring elements. These structuring elements may be flat (binary images or signals) or non flat (gray-scale images or signals). The pymorph Morphology Toolbox supports both kinds of structuring elements.

The pymorph Morphology Toolbox is supported in any python environment.

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Copyright (c) 2003, Roberto A. Lotufo, UNICAMP-University of Campinas; Rubens C. Machado, CenPRA-Renato Archer Research Center.