Object and Text Detection

Authors

  • Pooja Singh Department of Electronics Engineering, Thapathali Campus, Nepal
  • Richa Pokhrel Department of Electronics Engineering, Thapathali Campus, Nepal
  • Asmita Jha Department of Electronics Engineering, Thapathali Campus, Nepal
  • Pragya Jha Department of Electronics Engineering, Thapathali Campus, Nepal
  • Saroj Shakya Department of Electronics Engineering, Thapathali Campus, Nepal

DOI:

https://doi.org/10.3126/kjse.v7i1.60538

Keywords:

Region-Based Convolutional Neural Network (R-CNN), Region of Interest (ROI), Region Proposal Network (RPN), Google Text-to-Speech (gTTS)

Abstract

The main aim of our project is to develop a portable raspberry pi implemented gadget for object detection with relative motion and distance. This technology is basically used for conversion of sequence of real time objects into series of text which can be further stored into database and can be utilized to assist visually impaired people and in various security purposes as well. For that purpose, the conversion system is proposed in this project. Our system basically operates in 2 different modes. One is detecting the class of objects nearby with the help of R-CNN network, and the second one is obstacle detection using ultrasonic sensor. It includes 3 buttons for mode selection and the system operates on the basis of mode selection. It includes camera to capture an image as input, and input image is then passed to the R-CNN that recognizes number of objects inside image, their classes and types, text written inside and which is then can be passed to the database for a storage.

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Published

2023-05-01

How to Cite

Singh, P., Pokhrel, R., Jha, A., Jha, P., & Shakya, S. (2023). Object and Text Detection. KEC Journal of Science and Engineering, 7(1), 59–64. https://doi.org/10.3126/kjse.v7i1.60538

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Section

Articles