Automatic drug image identification system based on multiple image features

Authors:
Rung-Ching Chen;Cho-Tsan Pao;Ying-Hao Chen;Jeng-Chih Jian
Affiliations:
Department of Information Management Chaoyang University of Technology;Graduate Institute of Information, Chaoyang University of Technology;Department of Information Management Chaoyang University of Technology;Department of Information Management, Chaoyang University of Technology
Venue:
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part II
Year:
2010

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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.