Journal ArticleDOI
Image Segmentation Techniques
TLDR
There are several image segmentation techniques, some considered general purpose and some designed for specific classes of images as discussed by the authors, some of which can be classified as: measurement space guided spatial clustering, single linkage region growing schemes, hybrid link growing scheme, centroid region growing scheme and split-and-merge scheme.Abstract:
There are now a wide Abstract There are now a wide variety of image segmentation techniques, some considered general purpose and some designed for specific classes of images. These techniques can be classified as: measurement space guided spatial clustering, single linkage region growing schemes, hybrid linkage region growing schemes, centroid linkage region growing schemes, spatial clustering schemes, and split-and-merge schemes. In this paper, we define each of the major classes of image segmentation techniques and describe several specific examples of each class of algorithm. We illustrate some of the techniques with examples of segmentations performed on real images.read more
Citations
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Watersheds in digital spaces: an efficient algorithm based on immersion simulations
Luc Vincent,Pierre Soille +1 more
TL;DR: A fast and flexible algorithm for computing watersheds in digital gray-scale images is introduced, based on an immersion process analogy, which is reported to be faster than any other watershed algorithm.
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Object based image analysis for remote sensing
TL;DR: This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way.
Journal ArticleDOI
A review on image segmentation techniques
Nikhil R. Pal,Sankar K. Pal +1 more
TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
Journal ArticleDOI
Seeded region growing
Richard Adams,Leanne Bischof +1 more
TL;DR: This correspondence presents a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters, and suggests two ways in which it can be employed, namely, by using manual seed selection or by automated procedures.
Journal ArticleDOI
Current methods in medical image segmentation.
TL;DR: A critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images is presented, with an emphasis on the advantages and disadvantages of these methods for medical imaging applications.
References
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A survey on image segmentation
King-Sun Fu,J. K. Mui +1 more
TL;DR: This survey summarizes some of the proposed segmentation techniques in the area of biomedical image segmentation, which fall into the categories of characteristic feature thresholding or clustering and edge detection.
Journal ArticleDOI
Digital Step Edges from Zero Crossing of Second Directional Derivatives
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Color information for region segmentation
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Journal ArticleDOI
Clustering Using a Similarity Measure Based on Shared Near Neighbors
R. A. Jarvis,E.A. Patrick +1 more
TL;DR: A nonparametric clustering technique incorporating the concept of similarity based on the sharing of near neighbors is presented, which is an essentially paraliel approach and is applicable to a wide class of practical problems involving large sample size and high dimensionality.
Journal ArticleDOI
Region growing: Childhood and adolescence*
TL;DR: Region growing systems and their role in pictorial segmentation are reviewed; developmental trends relating these systems are examined and a global initialization technique is suggested.