Identifying music documents in a collection of images
Identifying music documents in a collection of images
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识别图像集中的音乐文档
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
T. Bell
中科院分区：
文献类型：
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作者：
D. Bainbridge;T. Bell
现在，数字库和搜索引擎可以根据查询找到许多文档的图像。搜索“贝多芬”将返回许多分数和手稿以及作曲家的图片。只能返回音乐分数。 ）评估了比率和霍夫变换。召回和精度分别为97.8％和88.4％，而HT在处理器时间方面达到了97.8％和73.5％。
Digital libraries and search engines are now well-equipped to find images of documents based on queries. Many images of music scores are now available, often mixed up with textual documents and images. For example, using the Google “images” search feature, a search for “Beethoven” will return a number of scores and manuscripts as well as pictures of the composer. In this paper we report on an investigation into methods to mechanically determine if a particular document is indeed a score, so that the user can specify that only musical scores should be returned. The goal is to find a minimal set of features that can be used as a quick test that will be applied to large numbers of documents. A variety of filters were considered, and two promising ones (run-length ratios and Hough transform) were evaluated. We found that a method based around run-lengths in vertical scans (RL) that out-performs a comparable algorithm using the Hough transform (HT). On a test set of 1030 images, RL achieved recall and precision of 97.8% and 88.4% respectively while HT achieved 97.8% and 73.5%. In terms of processor time, RL was more than five times as fast as HT.