| Summary: | 碩士 === 國立台北護理學院 === 資訊管理研究所 === 94 === With the elevation of peoples’ educational level and the occurrence of some serious medication mistakes, the need for correct pharmaceutical information and adequate knowledge of medication safety grows higher and higher. People often look for medicine information on the Internet or in books. However, they can only query using drug names or key words of medicine functions.
Images are often difficult to be described with text. From time to time, users who do not know the name of a medicine need to obtain the information of that medicine. In that circumstance, it’s a good method to enquire medicine information by recognizing medicines using computer vision. A content-based image retrieval method was proposed in this thesis. Shape, scale, and color features of pill images were extracted first and then fed into neural networks for classification. The pill image retrieval model was built by deploying appropriate features and neural networks to serve users.
After obtaining pill images via digital camera, features that represented the images were extracted automatically. The features were then processed for recognition. This thesis proposed a non-character-based method for medicine image retrieval to assist medical staffs and general users. It proved that a pill image recognition system using neural networks is feasible.
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