This paper explores the use of a learned classifier for post-OCR text correction. Experiments
with the Arabic language show that this approach, which integrates a weighted confusion …

Historical texts incorporate important characteristics that need to be assessed including
genre, text structure and content. Often overlooked are characteristics of handwritten …

Recognising characters from text have been a popular topic in the computer vision area. The
application can benefit to many problems in the world. For example: recognising text in …

In this paper, we present multi-font printed Arabic text recognition using hidden Markov
models (HMMs). We propose a novel approach to the sliding window technique for feature …

This study presents a novel approach for Arabic video text recognition based on recurrent
neural networks. In fact, embedded texts in videos represent a rich source of information for …

Text detection in videos is a challenging problem due to variety of text specificities, presence
of complex background and anti-aliasing/compression artifacts. In this paper, we present an …

The problem addressed in this paper is the classification and recognition of Arabic
handwritten characters. As a solution, we present a Neural Network (NN) architecture based …

Recognizing texts in video is more complex than in other environments such as scanned
documents. Video texts appear in various colors, unknown fonts and sizes, often affected by …

We present two algorithms that extend existing HMM parameter adaptation algorithms (MAP
and MLLR) by adapting the HMM structure. This improvement relies on a smart combination …

Character recognition is one of the most successful applications of artificial neural network
methods. However, most of the work has been dedicated to the recognition of Latin …