Range image feature extraction with varying degrees of data irregularity

被引：1

作者：

Suganthan, Shanmugalingam ^{[1
]}

Coleman, Sonya ^{[1
]}

Scotney, Bryan ^{[2
]}

机构：

[1] Univ Ulster, Sch Comp & Intelligent Syst, Magee, North Ireland

[2] Univ Ulster, Sch Comp & Informat Engn, Coleraine BT52 1SA, Londonderry, North Ireland

来源：

IMVIP 2007: INTERNATIONAL MACHINE VISION AND IMAGE PROCESSING CONFERENCE, PROCEEDINGS | 2007年

基金：

英国工程与自然科学研究理事会;

关键词：

D O I：

10.1109/IMVIP.2007.15

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The use of range images has become prominent in the field of computer vision. Due to the irregular nature of range image data that occurs with a number of sensors, edge detection techniques for range images are often based on scan line data approximations and hence do not employ exact data locations. We present a finite element based approach to the development of gradient operators that can be applied to both regularly and irregularly distributed range images. We have created synthetic irregularly distributed range images for each edge type, and the gradient operators developed are evaluated with respect to their performance in edge detection across varying levels of data irregularity.

引用

页码：33 / +

页数：3

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