There is a large collection of Handwritten English paper documents of Historical and Scientific importance. But paper documents are not recognised directly by computer. Hence the closest way of indexing these documents is by storing their document digital image. Hence a large database of document images can replace the paper documents. But the document and data corresponding to each image canno...

There are many ways to recognize the identity of individuals and authenticate them. Recognition and authentication of individuals with the help of their handwriting is regarded as a research topic in recent years. It is widely used in the field of security, legal, access control and financial activities. This article tries to examines the identification and authentication of individuals in Pers...

This work deals with poorly structured handwritten documents segmentation such as pages of handwritten notes produced with pen-based interfaces. We propose to use a formalism, based on Probabilistic Feature Grammars, that exhibit some interesting features. It allows handling ambiguities and to taking into account contextual information such as spatial relations between objects in the page.

Paleography experts spend many hours transcribing historic documents, and state-of-the-art handwritten text recognition systems are not suitable for performing this task automatically. In this paper we present the modifications on a previously developed interactive framework for transcription of handwritten text. This system, rather than full automation, aimed at assisting the user with the rec...

Separating text lines in handwritten documents remains a challenge because the text lines are often ununiformly skewed and curved. In this paper, we propose a novel text line segmentation algorithm based on Minimal Spanning Tree (MST) clustering with distance metric learning. Given a distance metric, the connected components of document image are grouped into a tree structure. Text lines are ex...

This paper presents a query-by-example word spotting in handwritten Arabic documents, based on Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representation. First the interest points are automatically extracted from the images using SIFT detector, then, we use SIFT descriptor to represent eac...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

In this paper, we describe our approach to extract salient events such as birth and death records from historical French parish documents that contain free-form handwritten text. The challenges posed by these documents to the current state of the art in handwriting recognition and information extraction go well beyond the generic challenges in recognizing handwritten text such as style variatio...

Signature has been one of the widely used verification biometrics out there. Handwritten signatures are in cheques, forms, letters, applications, minutes, etc. The every individual is unique nature, that why it essential a person’s handwritten signature be uniquely identified. Verification method for authenticating any during absence. Human prone to inaccuracy and sometimes indecisiveness. This...

Transcription of handwritten text documents is an expensive and timeconsuming task. Unfortunately, the accuracy of current state-of-the-art handwriting recognition systems cannot guarantee fully-automatic high quality transcriptions, so we need to revert to the computer assisted approach. Although this approach reduces the user effort needed to transcribe a given document, the transcription of ...