JOURNAL OF CRITICAL REVIEWS

ISSN- 2394-5125 VOL 7, ISSUE 12, 2020

OPTICAL CHARACTER RECOGNITION BASED SYNTHESIS SYSTEM USING OPEN CV

1M.SOWMIYA,2S.KANAGA SUBA RAJA, 3S.GNANAPRIYA,4AISWARYA5G GAYATHRI S,6 ISHA KRITHIKA G

1,3Assistant Professor, Department of Information Technology, Easwari Engineering College, Chennai,India Department of Information Technology, 2Associate Professor, Department of Information Technology, Easwari Engineering College, Chennai,India Department of Information Technology 4,5,6Easwari Engineering College Department of Information Technology Chennai, India

Received: 14 March 2020 Revised and Accepted: 4 July 2020

Abstract The idea presented on this paper is proposed for an application of the OCR. It acts as a life saver for the visually challenged people. The feature of this system is its ability to capture the image of a real world environment using a camera and recognize the characters present in that image being captured. This setup is constructed using OpenCv. The identified characters are converted into an audio file output which will be helpful for visually challenged people. The characters that have been identified in the representation captured from the device is converted to the string using Tesseract. The string is translated to articulate sound using printed form to articulate sound (TTS) module. Important feature of this OCR system is that this whole system is made portable in a way; it acts as an artificial vision for the blind through the audio output generated on the system. Keywords—Tesseract, OCR, OpenCv, TTS

I. INTRODUCTION In our planet of 6.5 billion humans, 265 million square measure visually impaired out of whom thirty-nine million folks square measure completely blind, i.e. haven't any vision in the least, and 225 million have delicate or severe vision defect (WHO, 2010). It’s been expected that by the the period 2022, these numbers can move on to seventy five hundreds blind and two hundred million people with vision defect [7]. The Blindness drastically affects one's ability to perform daily tasks or even their own needs. One major problem that any blind person goes through in everyday routine is their movement. Navigating from one place to another and identifying the things around them is an issue which makes their life complex. Hence vision becomes the primary requirement for a human being. In general, visually impaired people tries to assist themselves with the help of a simple cane or seek another person’s help to move from one place to another .It will be helpful in identifying any obstacle around them. However, what does a visually impaired person do when he wants to read something that is written somewhere around the particular user. It may be the name of a place he is standing or wanting to go or the name of a shop that he would like to visit by himself or simply any character written somewhere. Blind people so far have been aided with a method known as that gives them the ability to read and write on their own. However, that is not so effective. Braille is the traditional means of reading and writing whereas, OCR acts as a high tech tool helping the blind to read real character. Any Visually impaired person should be specifically trained in order to be familiar with such mechanisms. This paper has described the innovative plan additionally as low price technique that's accustomed hear the contents of the text image while not reading them. This method accustomed facilitate the blind folks to move with PC effectively through vocal interface. Text extraction from color image is very troublesome task for text to speech conversion system alphabets and numbers that are within the image victimisation the OCR technique and convert it into the format. This methodology encompass 2 components, image process module and voice process module. The optical character recognition (OCR) is that the method that converts the scan or printed text pictures into the text format for the any processing. This paper has bestowed the straightforward approach for text extraction and its conversion into speech. The testing of devices was conducted on openCV module. Text to speech (TTS) system produces the additional natural voice that can be closely matched with . The instance of the are the voice enabled e- mail and messaging.

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ISSN- 2394-5125 VOL 7, ISSUE 12, 2020

II. LITERATURE SURVEY a) Text to Speech The ADP methodology handed-down for the reason for which something is done or created is called an elocution trigger chips and can be operated in any medium. Alternative methodology evinces figurative rhetorical artist’s impression like relating to speech sounds transcriptions. S. Venkateswarlu 2016 put forward branch of knowledge effective use for printed form to articulate sounds combination in implanted methodology. The growing process potentiality of implanted appliance has given rise to the purview sure as shooting solicitation that would antecedently be dead in working area of computer screen milieu solely, to rove into worn podium. A vital distinctive attribute of the reckon methodology of contemporary continued progress is their assist for entreaty that move with the agent by connecting innate articulate sound wave. In their activity involved process, the conducting behavior of a printed form to articulate sound combined entreaty is judged on implanted processor framework and administered within the basal equipment podium square measure projected for real time conducting behavior refinement of the involved administration [6]. b) Optical Character Recognition

This paper bestowed their piece of research work for printed material discern and change the form into articulate sound appearance. Measure to check quality of appliance was browned on arduino. The Uno is at the start associated to the global network which provides variety of information perceived by VLAN. The program used by cp package is put in victimization peremptory lines. The primary methodology is to transfer the fixture libretto, ensuing control is to redevelop it to accomplish kind and also the end control initiates the scripts which will the remainder of the fixture exertion [1].The paper says they projected a tool to assist folks with sight weaken. During this project, we have a tendency to develop a tool that changes representation printed form to articulate sound format. This particulate purpose needed appliance. An important structure is this enforcement methodology, which takes into one’s possession an representation, removes only the region of interest and converts that printed form to articulate sound [2].This collaborative enterprise depicts a small part of quantity method for identification of printed form present within the representation victimization pi. The methodology program perceives of three defined the the : accession of image, preprocessing, extraction of printed form, printed material to articulate sound and articulate sound output [3]. This paper put forth the idea methodology victimization for studying the representation from stereotypic– like crescent probable presence, hospital presence, and motor vehicle arithmetic value [4]. Li Zhao et.al bestowed their work on Optical Character Recognition (OCR) investigate a refferal execution of the work on an occasional governance not specific impetus activity and establish the first small area with significant activity expression that occur an oversized a part of the latent period. They implemented and analyzed many program/step by procedure like i) many high threads, ii) Representation portfolio for a small area of significant activity iii) disparate program efficient.

They need used OCRopu0.3 as it is open supply computer code and supports modularity. RAST based analysis is employed that has vertical structure investigated printed form identification and perusal harmony disolve. OCR opus subsumes Tesseract as printed form remembrance device. The developed system needs high clarity pictures for economical results [5]. In all existing system image to text extraction is done using only optical character recognition with accuracy of 85% but in our proposed system OCR with open CV enhances the accuracy rate by 10%.

III. PROPOSED SYSTEM A. Overview As knowledge of literature is of main momentous within the diurnal regime (printed form being existed everyplace). Our methodology helps the ocular weakened by pronouncing them the printed form. In the planned system, we tend to develop AN economical printed form to articulate sound translation method by victimization the Arduino UNO. Once the printed representation was apprehend by the filmed device, the accustomed segregate the printed from the representation and so the Optical Character Recognition algorithm was enforced to acknowledge the written letters in the printed form and so the Arduino UNO was to translate that printed form into articulate sound by victimisation the collections. The proposed system is contains two processes: (i) Feed Image Extrication (ii) Matching Text Acquisition

Given diagram depicts the overall flow of system and contains major components. a) Overall Architecture Diagram

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ISSN- 2394-5125 VOL 7, ISSUE 12, 2020

Fig 3.1 Architecture Diagram B. Technique i) OCR Methodology Greatest in amount of the styles in identification of printed characters using photoelectric electronics go after a alteration of anatomical structure of this design. The core concept of the preliminary standardized part is to arrange the representation for conceding. Preliminary integral part contains two things, implied changes and social control. It subjected to some representation changes like sieving out uproar and extension the distinction. Then, the representation is segmental to distinguish the written symbol from one another. Chunk happens at 2 extent. On the primary extent, printed form, illustration and different components square measure discrete. On the ensuing extent, printed lines, turn of phrase and written letter within the representation are placed. Data indicating a cause fastens element inspection and forecast inspection will be accustomed abet printed form separation. Chunk is put forth by distinct attribute removal that is bothered with the illustration of the item.

Fig 3.2 Methodology

C. Workflow i) Feed Image Extrication

 The visually impaired person choses the capture mode.  Camera gets activated and captures the image present on the textbook:  Captured Image is stored in the separate in jpeg/jpg/png format.  The following activities takes place after image capturing  First: conversion of color image to grey scale which in turn is converted into binary image.  Second: Extraction of characters from grey image in given format.  Third: Removal of background from image  Fourth: Edge detection followed by writing the extracted text onto text document.

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Fig 3.3 Flow Diagram for Image to text conversion

ii) Matching Text Acquisition A Text-To-Speech (TTS) synthesizer is a computer-based system that ought to be ready to browse any text aloud. The diagram given below explains an equivalent. A text-to-speech system or engine consists of 2 parts: a front-end and a back- end. The front-end has 2 major tasks. First, it translates raw text containing , notation and symbols like numbers, special characters etc. into the insights. This method is typically referred to as text social control, pre-processing, or tokenization. The front-end assigns phonetic transcriptions to every , divides and marks the text into subdivide units, like phrases, clauses, and sentences. The method of distribution phonetic transcriptions to is named text-to- conversion. The server part refers to a synthesizer - then translates a symbolic linguistic illustration into sound.

Fig 3.4 Text to Speech Synthesis iii) Algorithm Input: captured image Output: text file Frame = getFrame; While 1 Frame_pre = Frame; Frame = getFrame; If similarity(Frame, Frame_pre) > ?1 & similarity(Frame, Background_img) < ?2 imageOutput = image scanning pixels of a text image from bottom to top and calculating F (i); check whether F (i) satisfies the first or second condition; Continue the second step until you finish the entire text image. End Complete the first condition (F (i)): If before the i-th line there are n continuous lines satisfying F (i)> s // threshold value Then the i-th line is the top edge of the text SecondCondition(F(s)): If before the i-th line there are continuous m lines satisfying F (i)> l // threshold value Then the ith line is the bottom edge of the text.

Captured image is fed into the OCR system using openCv library. Processed text extracted from image is stored in the separate file. Based on the text file audio is generated and played to the user. i) Input Image

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ISSN- 2394-5125 VOL 7, ISSUE 12, 2020

ii) Text Extraction

IV. EXPERIMENTAL RESULTS

S.No No. of Correct Correct image extraction of speech tests text synthesis 1 3 2 2 2 10 8 8 3 15 15 14 Table1: Results based on proposed system

96 94 92 90 88 Existing 86 Proposed 84 82 80 Existing Proposed

Fig4.1: Accuracy analysis between existing and proposed system

V. CONCLUSION This research project has initiated a method to change the form of a printed form to articulate sound using openCv and optical character recognition. The method comes up with a transferable and budgetary way of change form an representation to printed form. The duplex low level provides the client more prerogatives and extends the gamut of the client. The method facilitates a great exactness gait. Yield outcome have substantiated our supposition. At this point, the method changes form representation from English to English. In period of time following the moment, the detailed proposal is to use it as a several change in form. We also detailed proposal to contain as part of several activity like giving exemplar whenever a low standard representation is apprehend.

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