A Deep Learning Based Spontaneous Retail Product Identification - Tapa blanda

Sinopsis

Academic Paper from the year 2023 in the subject Computer Science - Commercial Information Technology, , language: English, abstract: The concept of self-service retail store has been successfully adopted around the world since its inception in 1916 United States of America. People carry their required retail products in a cart, hand-basket and make their purchase by standing in the queue to make payment. With advancements in electronics and computer sciences, this project aims to ease the "traditional purchase experience" at the same time maintaining the conventional "Hold-Observe-Purchase" experience by attempting to automate the billing procedure. Using deep learning algorithms and Image processing principles, the product images are recognized and its pertaining information is used to generate the transactional ledger as the products are added. This phase of the project aims at training our model to recognize custom images of Indian Retail products more specifically "Indian Consumable Retail products". Furthermore, the trained model is deployed on a "Single Board Computer (SBC)" such as "Raspberry Pi 4" to recognize the product images by taking its picture with the Raspberry Pi camera attached to the SBC and running the image through the trained model to identify it and generate the transaction ledger. Objectives: Primary objective to develop this project, was to eliminate the need of long payment queues especially in weekends in retail stores by automating the payment procedure. Implementing a complex principle of image recognition to promote "Digital payment revolution in India under atmanirbhar bharat" as predicted results are used to generate the transactional ledger. To learn and create a custom image data set of the retail products using data augmentation and image processing principles which is comprised of internet search results and photos captured by smart phone. To deploy a pre-trained image recognition algorithm (trained on Laptop computer) on a SBC such as raspberry pi attached with a camera which can capture image and can conveniently execute the pre trained model bypassing the need of advanced computation power.

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