An advanced Lab view based OCR system for hand written scripts

International Journal of Multidisciplinary Research and Development Online ISSN: 2349-4182 Print ISSN: 2349-5979 www.allsubjectjournal.com Volume 3; Issue 2; February 2016; Page No. 01-05

An advanced Lab view based OCR system for hand written scripts 1 1

Aruna Panda, 2 Prof. Mishra SN, 3 Prof. Das

M.Tech Scholar, Dept. of VLSI & Embedded Systems, KIIT, Bhubaneswar, India. 2, 3

Dept. of VLSI & Embedded Systems, KIIT, Bhubaneswar, Odisha, India.

Abstract Optical character recognition usually abbreviated to OCR, involves a computer system designed to translate images of typewritten text (usually captured by a scanner) into machine editable text or to translate pictures of characters into a standard encoding scheme representing them. OCR began as a field of research in artificial intelligence and computational vision. Character recognition is very interesting area of pattern recognition and it deals with offline handwriting recognition. Handwriting Recognition has continued to Persist as a suggests that of communication, collection, recording and sending data in regular life since the centuries even with the arrival of the new technologies. Machine recognition has several sensible applications, reading written communication envelopes, amount written in bank checks, bill processing, government records, industrial forms, signature verification, offline document recognition etc. In this paper we have implemented OCR for the Odia character recognition using the appearance based recognition technique. Formally, the problem can be stated as follows: given a training dataset x, and an object o, find object xj, within the dataset, most similar too. Our technique is an appearance based recognition giving satisfactory results Keywords: Odia Character Recognition, online, offline, pre-processing, classifiers. 1. Introduction India is a versatile country. In India over 20 official languages are there, Bengali, Malayalam, Hindi, English, Guajarati, Tamil, Kannada, Urdu etc [1]. Odia language is extremely popular language and it's a political candidate language of the Odisha State of India. More than 50 million people speak Odia language [2]. We tend to will notice that work has been done in the field of numerous languages like Chinese, Tamil, Telugu, and South Dravidian etc however terribly less work is done in the field of Odia language recognition. Pattern recognition has become a very interesting topic for researchers during last few decades. Typed characters will be simply recognized by laptop machine. But handwritten characters don't seem to be recognized efficiently and accurately by computer machine. Many researchers have done work to recognize these characters and many algorithms have been proposed to recognize characters. For over 30 years, researchers have been working on handwritten recognition. Over the few past years, the numbers of firms concerned in analysis on written recognition square measure increasing regularly. Challenges in handwritten characters recognition lie in the variation and distortion of offline handwritten characters since different people may use different style of handwriting. 2. Odia Script Odia-script used to write the Odia language. The Odia alphabet utilizes overall thirty distinct legitimate and recognized shapes, which mainly includes 59 Characters and 16 diacritics. There are many applications of this type of recognition. Like postal code verification, vehicle range plate recognition, bank cheque processing Assigning ZIP Codes to letter mail, Reading data entered in forms, e.g., tax forms, Automatic accounting procedures used in process utility bills, Verification of account

numbers, Automatic accounting of airline passenger tickets, Automatic validation of passports Etc [6]. In particular, machines that can read symbols are very cost effective. A machine that reads banking checks will method several additional checks than a human being in the same time. This type of application saves time and money, and eliminates the necessity that somebody's perform such a repetitive task [1]. Odia digits are having different characteristics. They are having various shapes and it’s really difficult to recognize those shapes. Due to varieties in shapes there are some characters that are confusing and possibilities for misclassification are very high [5]. Figure 1 shows the Odia alphabets and digits.

Fig 1: Odia Characters and Odia Digits

3. Application of Character Recognition System There are number of applications of Character Recognition System [1]. Task-specific Readers It is basically used for voluminous data processing. It focuses on the specific application like:  Assigning ZIP codes to letter mail.

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Reading data entered in forms, e.g. tax forms Verification of account numbers and courtesy amounts on bank checks Automatic accounting procedure used in processing utility bills Automatic accounting of airline passenger tickets Automatic validation of passports

Address Readers The address reader in a postal service reads the destination address block on the envelope and also reads the PIN code in the address block. Then using the PIN code it can sort the envelopes according to the area. Form Reader Form Reader automatically reads the data filled up in the form. It can find the printed and handwritten text in the form and also recognizes the same.

Check Reader Automatic check reader reads amount and account information from the check image and recognizes the amount as well as the account information. Signature verifier Just like check reader there is a signature verifier that also reads the signature image from the check image and recognizes the same. Bill Processing System This system is basically used to read payment slips, bills or any value specified in the bill. Passport Readers An automatic passport reader can be used for the inspection purpose. That can verify the traveler’s information like name, age, passport number and also photograph image which saves time at the airports.

Fig 2: Components of the character recognition system

4. Adopted Character Recognition Scheme The Pre-processing step aims to improve the image data or the image features that required for the further processing. The preprocessing is a series of operations performed on the scanned input image. It essentially enhances the image. It involves converting an input image to binary image, noise removing, dilation operation, line segmentation and digit segmentation and normalization [9]. Feature Extraction is a very important step for any character recognition system. This step involves the procedures like shape information or style which is very much useful for the classification of the pattern. The feature extraction stage analyses a text segment and selects a set of features that can be used to uniquely identify the text segment [10]. Classification stage uses the features extracted to identify the text segment according to the algorithm. The task is to compare the testing patterns and minimizing the error rate and correct classification of the pattern. Post-processing involves various approaches dictionary lookup and statistical approach or neural network recognition [11] for the correct recognition.

5. Lab view Based Implementations Lab view Lab View is a graphical programming language developed by National Instruments sometime in the mid to late 80’s by Jeff Kodosky. A program in Lab View is called a VI, which stands for Virtural Instrument. To create a VI, the programmer uses the Lab View programming environment to make the user interface by dragging and dropping objects, and arranging them as desired. To add functionality to the interface, the diagram, which resembles a flow chart is “wired” with the various structures and functions. So, in most Lab View programs, no lines of code are written, the functionality of the program is provided by the diagram. For this reason Lab View is called a graphical programming language. Ni Vision Assistance: Code Generation This step is simply creating a database of letters for the character recognition of a complete para and converting it into editable text format

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Fig 3: NI Vision Code generation

Ni Lab view based OCR Block

Fig 4: NI Lab view OCR block

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Ni Lab view Based OCR Front Panel

Fig 5: NI Labview OCR front panel

Editable Output for the Odia-OCR 5.

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6. Conclusion This paper presents the various steps involved in the Odia Optical character recognition system. It also describes the various applications of the character recognition system. Last section presents the proposed Labview based implementations for the Odia language OCR system from Code generation upto getting the editable text output.

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