Subword-based Stochastic Segment Modeling for Offline Arabic Handwriting Recognition

In this paper, we describe several experiments in which we use a stochastic segment model (SSM) to improve offline handwriting recognition (OHR) performance. We use the SSM to re-rank (re-score) multiple decoder hypotheses. Then, a probabilistic multi-class SVM is trained to model stochastic segments obtained from force aligning transcriptions with the underlying image. We extract multiple features from the stochastic segments that are sensitive to larger context span to train the SVM. Our experiments show that using confidence scores from the trained SVM within the SSM framework can significantly improve OHR performance. We also show that OHR performance can be improved by using a combination of character-based and parts-of-Arabic-words (PAW)-based SSMs

General Terms

POSTER PAPER. This paper proposes an approach of indexing and retrieving degraded handwritten documents. We present a modified version of the popular Vector Model in information retrieval (IR). Our model incorporates top n candidates from a HR system into the scheme of calculating the term frequency (tf) and the inverted document frequency (idf). Standardized IR Tests show that the proposed approach outperforms the retrieval of ordinary HR text in terms of mean average precision (MAP) and R-Precision

A cylindrical surface model to rectify the bound document image

This article proposes a novel approach on how to rectify the photo image of the bound document. The surface of the document is modeled by a cylindrical surface. By the geometry of camera image formation, the equations using the cue of directrixes to map the points on the surface in the 3-D scene to the points on the image plane are achieved. Baselines of the horizontal text line are extracted as projections of directrixes to estimate the bending extent of the surface, and then the images are rectified. The proposed method needs no auxiliary device. Experimental results are presented to demonstrate the feasibility and the application of the method. 1