Language-based document image retrieval for Trilingual System

Abstract

Language-based document image retrieval (LBDIR) is an essential need for a multi-lingual environment. It provides an ease of accessing, searching and browsing of the documents pertaining to a particular language. This paper proposes a method for LBDIR using multi-resolution Histogram of Oriented Gradient (HOG) features. These features are obtained by computing HOG on the sub-bands of Discrete Wavelet Transform. The Canberra distance is used for matching and retrieval of the documents. The proposed scheme is investigated on the three datasets (Dataset1, Dataset2 and Dataset3) consisting of 1437 document images of Kannada, Marathi, Telugu, Hindi and English languages. The objective of this work is to provide an efficient LBDIR for the government and non-government organizations of Karnataka, Maharashtra and Telangana states with the context of the tri-lingual model adopted. An average precision (AP) of 96.2%, 95.4%, 94.6%, 99.4% and 99.6% for Kannada, Marathi, Telugu, Hindi and English language documents is achieved while retrieving top 50 documents with the proposed method. The proposed feature extraction scheme provided promising results compared to existing techniques.