Parallelizing and Optimizing LIP-Canny Using NVIDIA CUDA

被引：0

作者：

Palomar, Rafael ^{[1
]}

Palomares, Jose M. ^{[1
]}

Castillo, Jose M. ^{[1
]}

Olivares, Joaquin ^{[1
]}

Gomez-Luna, Juan ^{[1
]}

机构：

[1] Univ Cordoba, Comp Architecture Area, Dept Comp Architecture Elect & Elect Technol, E-14071 Cordoba, Spain

来源：

TRENDS IN APPLIED INTELLIGENT SYSTEMS, PT III, PROCEEDINGS | 2010年 / 6098卷

关键词：

MODEL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Canny algorithm is a well known edge detector that is widely used in the previous processing stages in several algorithms related to computer vision. An alternative, the LIP-Canny algorithm, is based on a robust mathematical model closer to the human vision system, obtaining better results in terms of edge detection. In this work we describe LIP-Canny algorithm under the perspective from its parallelization and optimization by using the NVIDIA CUDA framework. Furthermore, we present; comparative results between an implementation of this algorithm using NVIDIA CUDA and the analogue using a C/C++ approach.

引用

页码：389 / 398

页数：10

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