Please use this identifier to cite or link to this item:
|Title:||Segmentation-free keyword spotting for handwritten documents based on heat kernel signature|
|Citation:||Zhang, X., Tan, C.L. (2013). Segmentation-free keyword spotting for handwritten documents based on heat kernel signature. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR : 827-831. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDAR.2013.169|
|Abstract:||We propose a new segmentation-free method for keyword spotting in handwritten documents based on Heat Kernel Signature (HKS). After key points are located by the key point detector for SIFT on the document pages and the query image, HKS descriptors are extracted from a local patch centered at each key point. In order to locate the positions where the query image appears in document pages, we present a searching method which tries to locate a local zone which contains enough matching key points corresponding to the query image. Our method does not need any pre-processing steps. © 2013 IEEE.|
|Source Title:||Proceedings of the International Conference on Document Analysis and Recognition, ICDAR|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 19, 2018
WEB OF SCIENCETM
checked on Sep 10, 2018
checked on Aug 17, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.