相关论文: uTHCD: A New Benchmarking for Tamil Handwritten OC…

Handwritten text recognition is an active research area in the field of deep learning and artificial intelligence to convert handwritten text into machine-understandable. A lot of work has been done for other languages, especially for…

Reading scene text, that is, text appearing in images, has numerous application areas, including assistive technology, search, and e-commerce. Although scene text recognition in English has advanced significantly and is often considered…

Offline Handwritten Text Recognition (HTR) systems play a crucial role in applications such as historical document digitization, automatic form processing, and biometric authentication. However, their performance is often hindered by the…

Script identification and text recognition are some of the major domains in the application of Artificial Intelligence. In this era of digitalization, the use of digital note-taking has become a common practice. Still, conventional methods…

Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cluster of high- and mid-resource scripts. We introduce GlotOCR Bench, a comprehensive…

Appropriate feature set for representation of pattern classes is one of the most important aspects of handwritten character recognition. The effectiveness of features depends on the discriminating power of the features chosen to represent…

Identification of minimum number of local regions of a handwritten character image, containing well-defined discriminating features which are sufficient for a minimal but complete description of the character is a challenging task. A new…

Direction properties of online strokes are used to analyze them in terms of homogeneous regions or sub-strokes with points satisfying common geometric properties. Such sub-strokes are called sub-units. These properties are used to extract…

In this paper, we propose a novel approach of word-level Indic script identification using only character-level data in training stage. The advantages of using character level data for training have been outlined in section I. Our method…

Handwritten font generation is important for preserving cultural heritage and creating personalized designs. It adds an authentic and expressive touch to printed materials, making them visually appealing and establishing a stronger…

Recognition of text on word or line images, without the need for sub-word segmentation has become the mainstream of research and development of text recognition for Indian languages. Modelling unsegmented sequences using Connectionist…

Oracle character recognition-an analysis of ancient Chinese inscriptions found on oracle bones-has become a pivotal field intersecting archaeology, paleography, and historical cultural studies. Traditional methods of oracle character…

Bangla language consists of fifty distinct characters and many compound characters. Several notable studies have been performed to recognize Bangla characters, both handwritten and optical. Our approach uses transfer learning to classify…

Handwritten text recognition is an open problem of great interest in the area of automatic document image analysis. The transcription of handwritten content present in digitized documents is significant in analyzing historical archives or…

OCR algorithms have received a significant improvement in performance recently, mainly due to the increase in the capabilities of artificial intelligence algorithms. However, this advancement is not evenly distributed over all languages.…

There are a lot of intensive researches on handwritten character recognition (HCR) for almost past four decades. The research has been done on some of popular scripts such as Roman, Arabic, Chinese and Indian. In this paper we present a…

A novel approach for recognition of handwritten compound Bangla characters, along with the Basic characters of Bangla alphabet, is presented here. Compared to English like Roman script, one of the major stumbling blocks in Optical Character…

There are many difficulties facing a handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, interconnections of neighbouring characters and their position in the…

Handwritten character recognition is a hot topic for research nowadays. If we can convert a handwritten piece of paper into a text-searchable document using the Optical Character Recognition (OCR) technique, we can easily understand the…

Document parsing is now widely used in applications, such as large-scale document digitization, retrieval-augmented generation, and domain-specific pipelines in healthcare and education. Benchmarking these models is crucial for assessing…