Recursive region segmentation by analysis of histograms
- 24 March 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Recursive segmentation of an image into regions using histograms is one of the most widely used techniques for image segmentation. At CMU, several versions of a region segmentation program have been developed based on this technique (Ohlander, Price, Shafer and Kanade). Based on these experiences, this paper discusses issues of recursive region segmentation in the context of PHOENIX, the newest version of region segmentation program, running on a VAX 11/780 under UNIX. The issues discussed in this paper include: Image features to be used in histogramming; comparison of the algorithm with other techniques; important improvements made in PHOENIX over its predecessor (Ohlander and Price); and some inherent problems in histogram-based segmentation together with suggestions for minimizing them. PHOENIX is being incorporated into the ARPA Image Understanding Testbed, under construction at SRI International.Keywords
This publication has 11 references indexed in Scilit:
- Semantic Description of Aerial Images Using Stochastic LabelingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1981
- Natural scene recognition using locus searchComputer Graphics and Image Processing, 1980
- Color information for region segmentationComputer Graphics and Image Processing, 1980
- Clustering edge values for threshold selectionComputer Graphics and Image Processing, 1979
- Recursive region extractionComputer Graphics and Image Processing, 1979
- Picture segmentation using a recursive region splitting methodComputer Graphics and Image Processing, 1978
- A sequential approach to the extraction of shape featuresComputer Graphics and Image Processing, 1977
- Picture Segmentation by a Tree Traversal AlgorithmJournal of the ACM, 1976
- An automated apparatus for cancer prescreening: CYBESTComputer Graphics and Image Processing, 1974
- A structural analyzer for a class of texturesComputer Graphics and Image Processing, 1973