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추가학습이 불필요한 이미지 특징 유사도 기반 상품 식별 시스템

Product Identification System based on Image Feature Similarity with Learning-free Model

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키워드

주제분류과학기술학

초록

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Abstract

Recently, logistics centers attempts to get help from artificial intelligence robots with hard labor. To generally perform picking task for robots, it is essential to detect and identify the product through the camera. Supervised learning-based deep learning technology is suitable for recognizing objects with high accuracy. But it has a disadvantage that requires a lot of time because a human must manually label the answer of the train image. In this paper, we propose a method that minimizes manual labor and makes it easy to add products. Our algorithm identifies the product with the highest similarity by calculating the similarity between the features of the input image and the features of the images in the product database. It does not require learning and labeling to identify a new product. To verify it, we test the algorithm by photographing a test product images in an environment that simulates a logistics site.

참고문헌 (25)

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