Book ChapterDOI
The Morphological Approach to Segmentation: The Watershed Transformation
Serge Beucher,Fernand Meyer +1 more
- pp 433-481
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TLDR
The principles of morphological segmentation will be presented and illustrated by means of examples, starting from the simplest ones and introducing step by step more complex segmentation tools.Abstract:
This chapter presents the principles of morphological segmentation Segmentation is one of the key problems in image processing In fact, one should say segmentations because there exist as many techniques as there are specific situations An original method of segmentation based on the use of watershed lines has been developed in the framework of mathematical morphology The chapter describes some useful morphological tools for segmentation: gradient, top-hat transform, distance function, geodesic distance function, and geodesic reconstructions The gradient image is used in the watershed transformation, because the main criterion for the segmentation in many applications is the homogeneity of the gray values of the objects present in the image The problems encountered in the segmentation process will be best illustrated by presenting a complete and typical segmentation problem in the field of automated cytology The oversegmentation produced by direct construction of the watershed line is due to the fact that every regional minimum becomes the center of a catchment basinread more
Citations
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Journal ArticleDOI
Detection of plant leaf diseases using image segmentation and soft computing techniques
Vijai Singh,Anoop Misra +1 more
TL;DR: An algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases and also covers survey on different diseases classification techniques that can be used for plant leaf disease detection.
Journal ArticleDOI
Segment-before-detect: Vehicle detection and classification through semantic segmentation of aerial images
TL;DR: This work presents a deep-learning based segment-before-detect method for segmentation and subsequent detection and classification of several varieties of wheeled vehicles in high resolution remote sensing images to show that deep learning is also suitable for object-oriented analysis of Earth Observation data as effective object detection can be obtained as a byproduct of accurate semantic segmentation.
Journal ArticleDOI
Versatile and efficient pore network extraction method using marker-based watershed segmentation.
TL;DR: An efficient algorithm for extracting networks using only standard image analysis techniques that correctly predicted the anisotropic permeability tensor from an image of fibrous media, demonstrating the critical ability to detect key structural features.
Proceedings ArticleDOI
Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy
TL;DR: This paper adopts and extends the approach to 3D volumes by using star-convex polyhedra to represent cell nuclei and similar shapes and demonstrates on two challenging datasets that the approach (StarDist-3D) leads to superior results when compared to classical and deep learning based methods.
Journal ArticleDOI
Automatic Breast Ultrasound Image Segmentation: A Survey
TL;DR: The basic ideas, theories, pros and cons of the approaches, group them into categories, and extensively review each category in depth by discussing the principles, application issues, and advantages/disadvantages are studied.
References
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Finding Edges and Lines in Images
TL;DR: This thesis is an attempt to formulate a set of edge detection criteria that capture as directly as possible the desirable properties of an edge operator.
Book
Précis d'analyse d'images
TL;DR: In this article, Parametres d'analyse d'images, morphologie mathematique, granulometrie, dispersion, anisotropie, niveaux de gris, erreurs, and anisotropic geometry are used.
Dissertation
Segmentation d'images et morphologie mathématique
TL;DR: In this article, the morphologie mathematique is used for the segmentation of images of gris and eaux, and the concept of marquage des regions a segmenter is introduced.
Journal ArticleDOI
On the use of the geodesic metric in image analysis
C. Lantuejoul,Serge Beucher +1 more
TL;DR: In this article, the authors defined the geodesic distance function (dX) as the greatest lower bound of the lengths of the arcs in a phase of a phase in a specimen.