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利用连续小波变换进行 TLC 图像的自动车道分割。

Automatic lane segmentation in TLC images using the continuous wavelet transform.

机构信息

INEB-Instituto de Engenharia Biomédica, Campus da FEUP, Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal ; Faculdade de Engenharia da Universidade do Porto (FEUP), 4200-465 Porto, Portugal.

出版信息

Comput Math Methods Med. 2013;2013:218415. doi: 10.1155/2013/218415. Epub 2013 Sep 19.

Abstract

This paper describes a new methodology for lane detection in Thin-Layer Chromatography images. An approach based on the continuous wavelet transform is used to enhance the relevant lane information contained in the intensity profile obtained from image data projection. Lane detection proceeds in three phases: the first obtains a set of candidate lanes, which are validated or removed in the second phase; in the third phase, lane limits are calculated, and subtle lanes are recovered. The superior performance of the new solution was confirmed by a comparison with three other methodologies previously described in the literature.

摘要

本文提出了一种用于薄层色谱图像中条带检测的新方法。该方法基于连续小波变换,用于增强从图像数据投影中获得的强度轮廓中包含的相关条带信息。条带检测分为三个阶段:第一阶段获得一组候选条带,在第二阶段对这些条带进行验证或去除;在第三阶段,计算条带边界,并恢复细微条带。通过与文献中先前描述的三种其他方法进行比较,验证了新解决方案的优越性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc4f/3792535/d0589d5bef09/CMMM2013-218415.001.jpg

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