AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE

March 2019
Vol-5, Issue-2
Paper ID: 9857
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Image processing eye glass database datasets visually challenged audio stream
Abstract
Visually challenged are majorly dependent on the Braille language for comprehensive reading of textual documents and their walking sticks they hold everyday for their obstruction identification. Making them virtually visible in an environment and get them workable in a technical organisation this system innovates the technology which provides audio descriptions of their blind surroundings. The design involves human face, object and textual recognition which make vision for visually challenged. The smart kit contains an eye glass provided with camera, an ear phone, a microphone and the system where the processing is carried out. The camera present at the nose head of eye glass captures the intended image of the user as snapshots and transfer to the system where it gets processed and produces the specified audio descriptions as output. The system's database holds a corresponding text for each image which is then converted to audio stream when sounded. In case of any mismatch or no entry of the image in the datasets then the new image is stored as new dataset with the name specified through microphone. This avoids mismatch of that image in the future search.

Author Information

# Name Institute / Affiliation
1 Kousalya R Panimalar Engineering College
2 Keerthana N Panimalar Engineering College
3 keertthana B Panimalar Engineering College
4 MRS.KAVITHA Panimalar Engineering College
5 SUBRAMANI Panimalar Engineering College

How to Cite

Use the following formats to cite this article in your research.

APA Style
R, Kousalya, N, Keerthana, B, keertthana, MRS.KAVITHA, & SUBRAMANI (2019). AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE. International Journal of Advance Research and Innovative Ideas In Education, 5(2), 1435-1441.
MLA Style
R, Kousalya, et al. "AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE." International Journal of Advance Research and Innovative Ideas In Education, vol. 5, no. 2, 2019, pp. 1435-1441.
IEEE Style
Kousalya R, Keerthana N, keertthana B, MRS.KAVITHA, and SUBRAMANI, "AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE," International Journal of Advance Research and Innovative Ideas In Education, vol. 5, no. 2, pp. 1435-1441, 2019.
Vancouver Style
R Kousalya, N Keerthana, B keertthana, MRS.KAVITHA, SUBRAMANI. AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE. International Journal of Advance Research and Innovative Ideas In Education. 2019;5(2):1435-1441.
Harvard Style
R, Kousalya, N, Keerthana, B, keertthana, MRS.KAVITHA, & SUBRAMANI (2019) 'AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE', International Journal of Advance Research and Innovative Ideas In Education, 5(2), pp. 1435-1441.
Chicago Style
R, Kousalya, et al. "AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE." International Journal of Advance Research and Innovative Ideas In Education 5, no. 2 (2019): 1435-1441.
Turabian Style
R, Kousalya, et al. "AUTOMATED OBJECT RECOGNIZATION FOR THE VISUALLY IMPAIRED PEOPLE." International Journal of Advance Research and Innovative Ideas In Education 5, no. 2 (2019): 1435-1441.

Export Citation

Related Research

A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
Vaibhav Ashok Bhangare et al. 2026 Computer Engineering
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
Vishakha Jadhav et al. 2026 Human Resource Management, Artificial Intelligence, Machine Learning, Payroll Systems, Cybersecurity, Business Intelligence, Robotic Process Automation, Employee Analytics, Digital Transforma
PDF Unavailable
Civic Engagement & Empowerment Platform
Supriya Dadaso Bankar et al. 2026 Computer engineering
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
Prof. Priyanka P. Kakade et al. 2026 Computer Engineering
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
Rohan Mulik et al. 2026 Computer Engineering
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
Kirti Datir et al. 2026 Computer Engineering
PDF Unavailable
Employee Performance Portal
P.Harika et al. 2026 Computer science and engineering
PDF Unavailable