From Ramp Discontinuities to Segmentation Tree

This paper presents a new algorithm for low-level multiscale segmentation of images. The algorithm is designed to detect image regions regardless of their shapes, sizes, and levels of interior homogeneity, by doing a multiscale analysis without assuming any prior models of region geometry. As in previous work, a region is modeled as a homogeneous set of connected pixels surrounded by ramp discontinuities. A new transform, called the ramp transform, is described, which is used to detect ramp discontinuities and seeds for all regions in an image. Region seeds are grown towards the ramp discontinuity areas by utilizing a relaxation labeling procedure. Segmentation is achieved by analyzing the output of this procedure at multiple photometric scales. Finally, all detected regions are organized into a tree data structure based on their recursive containment relations. Experiments on real and synthetic images verify the desired properties of the proposed algorithm.


Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Duzgun, Sebnem (2016-07-15)
This paper presents a vegetation detection application with semi-supervised target detection using hyperspectral unmixing and segmentation algorithms. The method firstly compares the known target spectral signature from a generic source such as a spectral library with each pixel of hyperspectral data cube employing Spectral Angle Mapper (SAM) algorithm. The pixel(s) with the best match are assumed to be the most likely target vegetation locations. The regions around these potential target locations are furt...
A Graph-Based Approach for Video Scene Detection
Sakarya, Ufuk; Telatar, Zjya (2008-04-22)
In this paper, a graph-based method for video scene detection is proposed. The method is based on a weighted undirected graph. Each shot is a vertex on the graph. Edge weights among the vertices are evaluated by using spatial and temporal similarities of shots. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. Temporal continuity constraint is achieved on this set. This set is the first detected video scene. The verti...
An image retrieval system based on region classification
Ozcanli, OC; Yarman-Vural, F (2004-01-01)
In this study, a content based image retrieval (CBIR) system to query the objects in an image database is proposed. Images are represented as collections of regions after being segmented with Normalized Cuts algorithm. MPEG-7 content descriptors are used to encode regions in a 239-dimensional feature space. User of the proposed CBIR system decides which objects to query and labels exemplar regions to train the system using a graphical interface. Fuzzy ARTMAP algorithm is used to learn the mapping between fe...
MRF Based Image Segmentation Augmented with Domain Specific Information
Karadag, Ozge Oztimur; Yarman Vural, Fatoş Tunay (2013-09-13)
A Markov Random Field based image segmentation system which combines top-down and bottom-up segmentation approaches is proposed in this study. The system is especially proposed for applications where no labeled training set is available, but some priori general information referred as domain specific information about the dataset is available. Domain specific information is received from a domain expert and formalized by a mathematical representation. The type of information and its representation depends o...
Low-level multiscale image segmentation and a benchmark for its evaluation
Akbaş, Emre (Elsevier BV, 2020-10-01)
In this paper, we present a segmentation algorithm to detect low-level structure present in images. The algorithm is designed to partition a given image into regions, corresponding to image structures, regardless of their shapes, sizes, and levels of interior homogeneity. We model a region as a connected set of pixels that is surrounded by ramp edge discontinuities where the magnitude of these discontinuities is large compared to the variation inside the region. Each region is associated with a scale that d...
Citation Formats
E. Akbaş, “From Ramp Discontinuities to Segmentation Tree,” 2009, vol. 5994, Accessed: 00, 2020. [Online]. Available: