WorldCIST'15 - 3rd World Conference on Information Systems and Technologies

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An Efficient and Adaptive Threshold of Volumetric Segmentation

Image segmentation plays a crucial role in effective understanding of digital images. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new and efficient method to detect visual objects from color spatial images and adaptive threshold. The presented method is a general-purpose volumetric segmentation algorithm and it produces good results. We present a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. This proposed volumetric graph-based segmentation method and we have presented the original and efficient algorithm of volumetric segmentation and prism cells used is the first run into volumetric segmentation algorithm. The advantage of using a virtual tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.

Author(s):

Dumitru Dan Burdescu    
University of Craiova
Romania

Marius Brezovan    
University of Craiova
Romania

Liana Stanescu    
University of Craiova
Romania

Cosmin STOICA SPAHIU    
University of Craiova
Romania

 

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