International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 02 | Feb -2017
e-ISSN: 2395 -0056
www.irjet.net
p-ISSN: 2395-0072
Product Label Reading System for visually challenged people Rahulkumar Chhatwani1, Arvind Langhe2, Akash Tikhe3 , Akshaysingh Chouhan4 Prof. S.V. Dabhade
Department of Computer Engineering, Smt. Kashibai Navale College of Engineering (SKNCOE), Savitribai Phule Pune University, Pune, India
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Abstract - With this project, we propose a camera-based
assistive text reading framework for helping blind persons in reading text labels from hand-held objects in their daily lives. To Isolate the object from backgrounds or other surrounding objects in the camera view ,we use Stroke Width Transform (SWT) technique. We first propose an efficient and effective method to define a region of interest (ROI) in an image of an object captured by using Camera. In the extracted ROI, text localization and recognition are performed for acquiring text information. For automatic localization of text regions from the extracted object’s Region Of Interest, we propose a text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels. Text characters are then converted into binary and recognized by off-the-shelf optical character recognition OCR software. We focus on user interface issues and try to achieve robustness of an algorithm while extracting and reading text from objects having complex backgrounds.
Key Words: Assistive Devices, Blindness, Edge pixels, Handheld objects, Optical Character recognition(OCR), Stroke Orientation, Region of interest(ROI) detection, Text localization, extraction and recognition, Stroke width Transform(SWT).
1. INTRODUCTION Reading is essential in today’s life. We see Printed text everywhere. It can be in reports, newspaper, receipts, bank slips, restaurant menu cards, product packages, medicine wrappers , etc. And while optical aids, video magnifiers, and screen readers can help blind users and those with low vision to access documents, there are few devices that can provide good access to common hand-held objects such as product packages, and objects printed with text such as prescription medication bottles. So people who are blind or have significant visual impairments to read printed labels will enhance independent living and foster economic and social self-sufficiency. Recent developments in computer vision ,digital cameras, and portable computers make it feasible to assist these individuals by developing camera-based products that combine computer vision technology with other existing commercial products such optical character recognition (OCR) systems. So, Product Label reading system is a system which helps blind persons to read text labels from hand-held objects in their daily lives. © 2017, IRJET
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Impact Factor value: 5.181
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To isolate the objects in the camera view, an efficient and effective method has been proposed to define a region of interest(ROI). In the extracted ROI, text localization and recognition are conducted to acquire text information. The recognized text codes are output to blind users in speech.
2. LITERATURE SURVEY Chucai Yi, Yingli Tian and Aries Arditi [1] proposed Portable Camera-Based Assistive Text and Product Label Reading From Hand-Held Objects for Blind Persons that totally focus recent developments in computer vision, digital cameras,and portable computers make it feasible to assist these individuals by developing camera-based products that combine computer vision technology with other existing commercial products such optical character recognition (OCR) systems. Karen Duarte, Jos´e Cec´ılio, Jorge S´a Silva, Pedro Furtado [2] proposed Information and Assisted Navigation System that aims to highlight the user’s device integrating it with devices and technologies already used by users, as their own smartphone. Ender Tekin and James M. Coughlan [3] proposed an algorithm enabling blind users to find and read barcodes. In this paper, the ability of people who are blind or have significant visual impairments to read printed labels and product packages will enhance independent living and foster economic and social self-sufficiency. Sunil Kumar, Rajat Gupta, Nitin Khanna, Santanu Chaudhury and Shiv Dutt Joshi [4] proposed Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model. This paper proposes scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estimating globally matched wavelet filters using a collection of ground truth images and text extraction scheme. Kwang In Kim, Keechul Jung, and Jin Hyung Kim[5] proposed Texture-Based Approach for Text Detection in Images Using SVM and Continuously Adaptive Mean Shift Algorithm. This paper show texture-based method for detecting texts in images. A support vector machine (SVM)
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