Segmentation of Text/Graphic from Handwritten Mathematical Documents Using Gabor Filter

Most of handwritten mathematical documents contain graphics in addition to mathematical text. Thus, these documents must be segmented into homogenous areas to facilitate their digitization. Text and graphic segmentation from these documents aims at segmenting the document into two blocks: the first contains the texts and the second includes the graphical objects. In this paper, we focus our interest on document segmentation based on the texture and precisely the frequency methods. These methods are ideal to characterize the texture and allow detecting the frequencies and orientations characteristics. Firstly, we present the main steps of our system (pre-processing, features extraction (using Gabor filter), post-processing and text/graphic segmentation). Secondly, we discuss and interpret the results obtained by our system.