Flat zones filtering, connected operators, and filters by reconstruction

This correspondence deals with the notion of connected operators. Starting from the definition for operator acting on sets, it is shown how to extend it to operators acting on function. Typically, a connected operator acting on a function is a transformation that enlarges the partition of the space created by the flat zones of the functions. It is shown that from any connected operator acting on sets, one can construct a connected operator for functions (however, it is not the unique way of generating connected operators for functions). Moreover, the concept of pyramid is introduced in a formal way. It is shown that, if a pyramid is based on connected operators, the flat zones of the functions increase with the level of the pyramid. In other words, the flat zones are nested. Filters by reconstruction are defined and their main properties are presented. Finally, some examples of application of connected operators and use of flat zones are described.Peer ReviewedPostprint (published version

Stereo image analysis using connected operators

Connected operators are increasingly used in image processing due to their properties of simplifying the image with various criteria, without loosing contour's information. These properties are related to the connected operator approach that either preserves or completely eliminates a determined connected component, according to an established criterion of analysis. In this paper we will define a new connected operator for stereo images. The goal is to simplify one of the images (left) in the sense that the operator will eliminate the image components that are not present at a determined location in the other image (right). This filter let us select in a stereo image, objects as a function of their distance from the observer (for instance used in auto guided vehicles).Peer ReviewedPostprint (published version

Morphological operators for very low bit rate video coding

This paper deals with the use of some morphological tools for video coding at very low bit rates. Rather than describing a complete coding algorithm, the purpose of this paper is to focus on morphological connected operators and segmentation tools that have proved to be attractive for compression.Peer ReviewedPostprint (published version

Morphological Filtering in Shape Spaces: Applications using Tree-Based Image Representations

Connected operators are filtering tools that act by merging elementary regions of an image. A popular strategy is based on tree-based image representations: for example, one can compute an attribute on each node of the tree and keep only the nodes for which the attribute is sufficiently strong. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is done not in the space of the image, but on the space of shapes build from the image. Such a processing is a generalization of the existing tree-based connected operators. Indeed, the framework includes classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on shape attributes. Finally, we also propose a novel class of self-dual connected operators that we call morphological shapings.Comment: 4 pages, will appear in 21st International Conference on Pattern Recognition (ICPR 2012

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-

Accurate and fast 3D interactive segmentation system applied to MR brain quantification

This work presents an efficient interactive segmentation system for volumetric data-sets based on advanced 3D morphological analyses and an interaction paradigm that allows a good match with user intentions. This system has been designed to produce accurate results under the complete control of the user, to minimize the interaction time and to address a generality of 3D segmentation tasks. The system has been tested and compared with other softwares on normal MR brain structure quantification and on a challenging clinical setting pointed to the detection of the presence of subtle brain atrophy associated to primitive immunodeficiency (PID)

Metamaterial formalism approach for advancing the recognition of glioma areas in brain tissue biopsies

Early detection of a tumor makes it more probable that the patient will, finally, beat cancer and recover. The main goal of broadly defined cancer diagnostics is to determine whether a patient has a tumor, where it is located, and its histological type and severity. The major characteristic of the cancer affected tissue is the presence of the glioma cells in the sample. The current approach in diagnosis focuses mainly on microbiological, immunological, and pathological aspects rather than on the “metamaterial geometry” of the diseases. The determination of the effective properties of the biological tissue samples and treating them as disordered metamaterial media has become possible with the development of effective medium approximation techniques. Their advantage lies in their capability to treat the biological tissue samples as metamaterial structures, possessing the well-studied properties. Here, we present, for the first time to our knowledge, the studies on metamaterial properties of biological tissues to identify healthy and cancerous areas in the brain tissue. The results show that the metamaterial properties strongly differ depending on the tissue type, if it is healthy or unhealthy. The obtained effective permittivity values were dependent on various factors, like the amount of different cell types in the sample and their distribution. Based on these findings, the identification of the cancer affected areas based on their effective medium properties was performed. These results prove the metamaterial model capability in recognition of the cancer affected areas. The presented approach can have a significant impact on the development of methodological approaches toward precise identification of pathological tissues and would allow for more effective detection of cancer-related changes

Segmentation and feature extraction of fluid-filled uterine fibroid–A knowledge-based approach

Uterine fibroids are the most common pelvic tumours in females. Ultrasound images of fibroids require image segmentation and feature extraction for analysis. This paper proposes a new method for segmenting the fluid-filled fibroid found in the uterus. It presents a fully automatic approach in which there is no need for human intervention. The method used in this paper employs a number of knowledge-based rules to locate the object and also utilises the concepts in mathematical morphology. It also extracts the necessary features of the fibroid which can be used to prepare the radiological report. The performance of this method is evaluated using area-based metrics