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Automatic Shoe Detection Using Image Processing

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Innovations in Bio-Inspired Computing and Applications (IBICA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 419))

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Abstract

Image processing is a technique for applying operations on an image in order to improve it or extract relevant information from it. Object detection is a computer vision approach for identifying and locating things in images and videos. Deep learning has showed enormous promise in a wide range of real-world applications. Recent object detection based on image processing and deep learning models has yielded promising results in terms of object detection in images. Educational institutes and industries are insisting students and employees to wear shoes to enhance their safety and as well as for the professional appearance. It is observed that some of the students or employees are not wearing shoes which may lead to some serious injuries at labs and work places . To avoid this institutions and industries are involving with the physical verification process. The physical verification process is overhead to them. The intension of the proposed work is to automate the shoe detecting process using image processing and deep learning techniques. A shoe detection dataset consists of with shoe images which has been used to train model. The trained model is used to identify whether the person is wearing shoes or not in real time. If the person is not wearing shoe then the appropriate notification will be given. This proposed work will be helpful to the industries or institutions to ensure the safety measures.

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Prasanna Kumar, K.R., Pravin, D., Rokith Dhayal, N., Sathya, S. (2022). Automatic Shoe Detection Using Image Processing. In: Abraham, A., et al. Innovations in Bio-Inspired Computing and Applications. IBICA 2021. Lecture Notes in Networks and Systems, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-96299-9_26

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