Iamxt: max-tree toolbox for image processing and analysis

The iamxt is an array-based max-tree toolbox implemented in Python using the NumPy library for array processing. It has state of the art methods for building and processing the max-tree, and a large set of visualization tools that allow to view the tree and the contents of its nodes. The array-based programming style and max-tree representation used in the toolbox make it simple to use. The intended audience of this toolbox includes mathematical morphology students and researchers that want to develop research in the field and image processing researchers that need a toolbox simple to use and easy to integrate in their applications68184CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP311228/2014-32013/23514-0; 2013/07559-

Interactive image manipulation using morphological trees and spline-based skeletons

The ability to edit an image using intuitive commands and primitives is a desired feature for any image editing software. In this paper, we combine recent results in medial axes with the well-established morphological tree representations to develop an interactive image editing tool that provides global and local image manipulation using high-level primitives. We propose a new way to render interactive morphological trees using icicle plots and introduce different ways of manipulating spline-based medial axis transforms for grayscale and colored image editing. Different applications of the tool, such as watermark removal, image deformation, dataset augmentation for machine learning, artistic illumination manipulation, image rearrangement, and clothing design, are described and showcased on examples

Interactive max-tree visualization tool for image processing and analysis

Orientador: Roberto de Alencar LotufoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A árvore máxima, no inglês max-tree, é uma poderosa estrutura de dados que representa hierarquicamente os componentes conexos resultantes de todos os thresholds de uma imagem, tem sido utilizada em muitas aplicações de análise e processamento de imagens. A max-tree de uma imagem natural tipicamente possui milhares de nós, o que dificulta construir uma representação gráfica de sua estrutura completa. Propomos uma metodologia para a construção de uma representação gráfica interativa da max-tree, possibilitada por um processo de simplificação que reduz o número de nós da max-tree e preserva os nós mais relevantes. Nossa representação exibe uma árvore máxima simplificada, mas seus recursos interativos permitem ao usuário navegar por todos os nós da max-tree original, visualizar seus componentes conexos e criar sub-conjuntos de nós. Nós demonstramos o potencial da nossa ferramenta para problemas de análise, segmentação e filtragem. Nossa aplicação também é uma ferramenta educativa para o estudo da max-tree e suporte para o planejamento de métodos automáticosAbstract: The max-tree is a powerful data structure that represents all possible upper thresholds of an image, it has been successfully used in many image processing and analysis applications. The max-tree corresponding to a natural image usually has thousands of nodes, making it difficult to build a graphical representation of its complete structure. We propose a methodology for building an interactive graphical representation of the max-tree, made possible by a process of simplification which reduces the number of max-tree nodes preserving the most relevant nodes. Our representation displays a simplified max-tree, but its interactive features allow the user to navigate through all the nodes of the original max-tree, visualize its connected components and create sub-sets of nodes. We demonstrate the potential of our tool for analysis, segmentation and filtering tasks. Our application is also an educational tool for the learning of max-tree and it provides insight for the development of automatic methodsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric