A Web-based Image Recognition System for Detecting Harumanis Mangoes

Authors

  • Romiza Md Nor Universiti Teknologi MARA
  • Mohamad Shahmil Saari Universiti Teknologi MARA Perlis
  • Huzaifah A Hamid Universiti Teknologi MARA Perlis

Keywords:

image recognition, fruit texture, convolutional neural networks

Abstract

Convolutional neural networks are popular today because of their specialty in the recognition of the image. It also can be thought of as an automatic feature extractor from the image. Therefore, this project is developed to recognize the mango type based on its texture. In this project, the framework that is used is TensorFlow and Keras and it is written using Python language. This project will use Mobile Net architecture model because it consumes less computational power and it also can provide efficiency of the accuracy. CamPauh is developed to recognize four classes of mango which are Harumanis, apple mango, other type of mangoes and not mango. CamPauh is a web-based where users ca recognized the mango and the result will be stored into the database and it will appear on the website. In this paper evaluation on the accuracy is discussed to support users’ satisfaction in identifying the correct mango type.

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Published

2020-11-02

How to Cite

Md Nor, R., Saari, M. S., & A Hamid, H. (2020). A Web-based Image Recognition System for Detecting Harumanis Mangoes . Journal of Computing Research and Innovation, 5(4), 48-53. Retrieved from https://crinn.conferencehunter.com/index.php/jcrinn/article/view/153

Issue

Section

General Computing

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