A Novel Approach of Adaptive Thresholding for Image Segmentation on GPU

被引：0

作者：

Upadhyay, Pawan Kumar ^{[1
]}

Chandra, Satish ^{[1
]}

Sharma, Arun ^{[2
]}

机构：

[1] Jaypee Inst Informat Technol, Comp Sci & Engn, Noida, India

[2] SUNY Buffalo, Comp Sci & Engn, Buffalo, NY USA

来源：

2016 FOURTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (PDGC) | 2016年

关键词：

Image segmentation; Adaptive thresholding; GPU; Exponential Entropy; Dermoscopy images;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the recent decades, graphical processing unit (GPU) improvises the programmability in the area of image processing for reducing the computational time as compare to CPU. GPUs can solve large data parallel problems and tends to give most robust and energy efficient segmentation method. It also gives the concept of memory pre-allocation and vectorization and handled the large image data set very profoundly for accelerated image segmentation method. In this paper, investigation results are obtained on 100 gold standard dermoscopy images which reveal that the proposed novel method of image segmentation is benefited from GPU processing in terms of speed and accuracy for lesion detection.

引用

页码：652 / 655

页数：4

共 14 条

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