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An Intelligent Image Classification Approach for Food Items Nutrition Facts

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Second International Conference on Image Processing and Capsule Networks (ICIPCN 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 300))

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Abstract

Nutrition is essential for health and wellbeing. The state of health is determined by what one eats. Knowing the nutrient contents of food create awareness of what to eat and how much to eat. People are growing fond of the modern lifestyle and they merely eat to fill up their stomach. The UN report states that over 25 percent of the world’s population lack nutritious food. Lack of balanced diet may lead to obesity and other health related issues. Study further reveals that through appropriate diet and daily food consumption tracking, even obese people showed remarkable reduction in weight. Inspired by these findings in literature, a mobile application has been proposed to identify and classify Indian breakfast food items using a derivative of the Convolution Neural Network model called MobileNet. The identified images are further classified to determine the nutritive content in the food identified. In addition, the mobile App also summarizes the daily nutritional value of food consumed against the recommended nutritional value based on gender. Thus, the proposed work can be extended to monitor the daily food habits of people with health conscious and related issues.

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Author information

Authors and Affiliations

  1. Sri Ramakrishna Engineering College, Coimbatore, India

    Preethi Harris, M. Nithin, S. Nithish Kannan, R. Gokul Prasanth & M. Kissore Kumar

Authors
  1. Preethi Harris
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  2. M. Nithin
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  3. S. Nithish Kannan
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  4. R. Gokul Prasanth
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  5. M. Kissore Kumar
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Corresponding author

Correspondence to Preethi Harris .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan

    Joy Iong-Zong Chen

  2. Departamento de Engenharia Mecanica, Universidade do Porto, Porto, Portugal

    JoĂŁo Manuel R. S. Tavares

  3. College of Engineering, Prince Sattan Bin Abdulaziz University, Al-Kharj, Saudi Arabia

    Abdullah M. Iliyasu

  4. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

    Ke-Lin Du

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Harris, P., Nithin, M., Kannan, S.N., Prasanth, R.G., Kumar, M.K. (2022). An Intelligent Image Classification Approach for Food Items Nutrition Facts. In: Chen, J.IZ., Tavares, J.M.R.S., Iliyasu, A.M., Du, KL. (eds) Second International Conference on Image Processing and Capsule Networks. ICIPCN 2021. Lecture Notes in Networks and Systems, vol 300. Springer, Cham. https://doi.org/10.1007/978-3-030-84760-9_37

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