Recent Advances in Video Based Document Processing: A Review

Abstract

Extraction and recognition of text present in video has become a very popular research area in the last decade. Generally, text present in video frames is of different size, orientation, style, etc. with complex backgrounds, noise, low resolution and contrast. These factors make the automatic text extraction and recognition in video frames a challenging task. A large number of techniques have been proposed by various researchers in the recent past to address the problem. This paper presents a review of various state-of-the-art techniques proposed towards different stages (e.g. detection, localization, extraction, etc.) of text information processing in video frames. Looking at the growing popularity and the recent developments in the processing of text in video frames, this review imparts details of current trends and potential directions for further research activities to assist researchers.

ATHENA: Automatic text height extraction for the analysis of old handwritten manuscripts

“…A huge amount of work has been presented to deal with segmentation [6], line extraction [7], char and word spotting [8], [9], and classification of handwritten manuscripts [10], [11]. An exhaustive review is far outside the scope of the paper, and the reader is referred to various recent surveys [12], [13]. Here, we discuss only the techniques closely related to ours.…”

Athena

“…A huge amount of work has been presented to deal with different aspects ranging from segmentation [Grana et al 2009], line extraction [Jindal and Lehal 2012], char and word spotting Yalniz and Manmatha 2012], and classification of handwritten documents and medieval manuscripts [Louloudis et al 2008;Leydier et al 2007]. An exhaustive review of the literature is far outside the scope of the article, and the reader is referred to the seminal work of Nagy [2000], which gives an overview of early techniques proposed for text segmentation, OCR and background removal, and various recent surveys [Sharma et al 2012;Likforman-Sulem et al 2007]. Here we discuss only the state-of-the-art techniques closely related to ours.…”

T-HOG: An effective gradient-based descriptor for single line text regions

“…An exhaustive review of this work is far outside the scope of the paper, and the reader is referred to the survey of Sharma et al [15], that covers some advances in this area. Recently some text detectors, such as the one described by Anthimopoulos et al [21] in 2010, have used descriptors based on multiscale local binary patterns (LBP) introduced by Ojala et al [22].…”