Line detection methods for spectrogram images

被引：0

作者：

Lampert, Thomas A. ^{[1
]}

O’Keefe, Simon E. M. ^{[1
]}

Pears, Nick E. ^{[1
]}

机构：

[1] Department of Computer Science, University of York, York

来源：

Advances in Intelligent and Soft Computing | 2009年 / 57卷

关键词：

D O I：

10.1007/978-3-540-93905-4_16

中图分类号：

学科分类号：

摘要：

Accurate feature detection is key to higher level decisions regarding image content.Within the domain of spectrogram track detection and classification, the detection problem is compounded by low signal to noise ratios and high track appearance variation. Evaluation of standard feature detection methods present in the literature is essential to determine their strengths and weaknesses in this domain. With this knowledge, improved detection strategies can be developed. This paper presents a comparison of line detectors and a novel linear feature detector able to detect tracks of varying gradients. It is shown that the Equal Error Rates of existing methods are high, highlighting the need for research into novel detectors. Preliminary results obtained with a limited implementation of the novel method are presented which demonstrate an improvement over those evaluated. © Springer-Verlag Berlin Heidelberg 2009.

引用

页码：127 / 134

页数：7

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