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Author | David Aldavert; Marçal Rusiñol | ||||
Title | Manuscript text line detection and segmentation using second-order derivatives analysis | Type | Conference Article | ||
Year | 2018 | Publication | 13th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages | 293 - 298 | ||
Keywords | text line detection; text line segmentation; text region detection; second-order derivatives | ||||
Abstract | In this paper, we explore the use of second-order derivatives to detect text lines on handwritten document images. Taking advantage that the second derivative gives a minimum response when a dark linear element over a
bright background has the same orientation as the filter, we use this operator to create a map with the local orientation and strength of putative text lines in the document. Then, we detect line segments by selecting and merging the filter responses that have a similar orientation and scale. Finally, text lines are found by merging the segments that are within the same text region. The proposed segmentation algorithm, is learning-free while showing a performance similar to the state of the art methods in publicly available datasets. |
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Address | Viena; Austria; April 2018 | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.084; 600.129; 302.065; 600.121;ADAS | Approved | no | ||
Call Number | Admin @ si @ AlR2018a | Serial | 3104 | ||
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