Top Research Papers on OCR

This article examines OCR in four different ways, providing detailed information about the difficulties that may arise during OCR, and examines the general stages of OCR systems such as preprocessing, segmentation, normalization, normalization and extraction.

This paper presents a simple, efficient, and less costly approach to construct OCR for reading any document that has fix font size and style or handwritten style and uses database to recognize English characters which makes this OCR very simple to manage.

The main objectives of this paper are to develop the classification, identification of deference prototyping for written and printed consonants, conjunct consonants and symbols based on 3 layered approaches with different measurable area by using fuzzy logic and to determine suitable features for handwritten character recognition.

This work aimed to develop a character recognition method to facilitate the correction of answer cards in the Multiprova software through the development of a response card analysis flow that would culminate in the recognition of letters written by students and automatic correction of the tests. To isolate and identify the answers written on the answer cards, image segmentation techniques were used based on fixed marks printed on the cards. To recognize the letters and numbers written on the cards, trained three convolutional neural networks (for digits, letters and true or false). The results...

A novel technique is proposed for automated OCR based on multi-properties features fusion and selection that will help for license plate recognition and text conversion from a printed document to machine-readable.

Kalkulator merupakan alat bantu hitung yang ditemukan oleh seorang matematikawan Prancis pada tahun 1642 yaitu Blaise Pascal. Hingga saat ini, perkembangan kalkulator telah berevolusi mulai dari segi ukuran, fitur, hingga performa kecepatan hitung yang semakin canggih. Penggunaan kalkulator dapat memudahkan manusia dalam melakukan operasi hitung aritmatika. Saat ini, terdapat kendala masalah pada proses pemasukan angka pada kalkulator sebagai contoh jika kita ingin menghitung nilai dari angka-angka pada media tulis seperti kertas, papan tulis atau media tulis lainnya, pengguna harus terlebih d...

The project effort resulted in an evaluation of a correlation technique as implemented in an existing computer software program, as applied to automatic recognition of typeset printed characters which were sampled and digitized on a high-resolution scanner.

This project enhances the character recognition system by using Linear Support Vector to enhance ease usability of programmed evaluation framework and improvise it with the help of SVM, Machine learning & Artificial intelligence.

To decrease erroneous read and to improve a recognition ratio, even when a read object character comes into contact with an underline, or when it is surrounded by a frame.

Computer-based optical character recognition systems allow blind persons access to a wide variety of printed material and the features that should be considered before one purchases them are described.

Dr. Mori from the Ricoh R&D Center in Japan has used his experience in optical character recognition to create a thorough reference to this widely used but still growing technology.

In the second method, features extracted from the segmented characters are used to train the SVM classifiers, which are later tested by a test set of handwritten digits.

To prevent a recognition error by setting a character frame to be the reference of character segmentation and to ensure character recognition and the recognition of the position of the character frame by clearly classifying the character color and the color of thecharacter frame.

After classification and training the identified characters are grouped to reconstruct the original symbol strings, and various algorithms may then be applied to detect and correct errors.

Optical character recognition is a process by which printed text is detected and transformed into a computer text file that is readable by word processor, statistics, and/or database software supported by the OCR program used.

Optical character recognition (OCR) is the name given to the automatic reading process, by machine, of printed and perhaps even handwritten text, where the initial transfer of information from the page is by purely optical means. This definition, which excludes processes in which the marks on the paper are sensed in other ways, for example magnetically, does not rule out some cooperation by the writer or printer, for example by using special printing founts or styles.

My company, Southdata Ltd., is interested in OCR (Optical Character Recognition), and the first problem you have is getting from the paper document in the source language onto a computer so that you can work at it.

The character recognition method is presented by using OCR technology and android phone with higher quality camera and the objective is to develop user friendly application which performs image to speech conversion system using android phones.

To achieve efficiency and less computational cost, OCR in this paper uses database to recognize English characters which makes this OCR very simple to manage.

The sections in this article are OCR Systems, Segmentation–Dissection Techniques, Recognition of Segmented Characters, Contextual Postprocessing, and State of the Art in OCR.