Segmentation-Based Historical Handwritten Word Spotting Using Document-Specific Local Features

Many word spotting strategies for the modern documents are not directly applicable to historical handwritten documents due to writing styles variety and intense degradation. In this paper, a new method that permits effective word spotting in handwritten documents is presented that relies upon document-specific local features which take into account texture information around representative key points. Experimental work on two historical handwritten datasets using standard evaluation measures shows the improved performance achieved by the proposed methodology.