Text-Line Extraction Using a Convolution of Isotropic Gaussian Filter with a Set of Line Filters

Text-line extraction is a key task in document analysis. Methods based on an isotropic Gaussian filtering and ridge detection have shown good results. This paper describes performance improvements to these technique based on the use of a convolution of isotropic Gaussian filter with line filters. These new filter banks are motivated by a matched filter approach to text-lines and, in addition, require fewer operations to compute. We evaluate the performance of the new filter bank in combination with ridge detection on the public DFKI-I (CBDAR 2007 dewarping contest) dataset, which contains camera captured document images and demonstrate improvements in performance to previous state-of-the-art techniques.