Abstract
Drugs can be divided into many types, such as different compositions, content and shapes, but users do not always possess or comprehend professional drug facts. Many drug recognition systems offer keyword search but they are difficult for users to understand the medications’ names. One possible way would be for users to describe the features of drugs according to their appearance, such as color, shape, etc. In this paper, we propose an automatic drug image identification system (ADIIS) based on multiple image features. ADIIS is able to improve drug identification errors as well as provide drug information. In our primary experiments, by using an image, the system was able to retrieve the top ten similar drugs for the user to identify the specific drug. In addition, out of the ten identified drugs retrieved by ADIIS, the first of the ten drug identifications was 95% of the correct match.
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Chen, RC., Pao, CT., Chen, YH., Jian, JC. (2010). Automatic Drug Image Identification System Based on Multiple Image Features. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_27
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DOI: https://doi.org/10.1007/978-3-642-16732-4_27
Publisher Name: Springer, Berlin, Heidelberg
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