International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Shuang Li, Jun Sasaki*

Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan


 

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ABSTRACT


Many people go sightseeing based on the information available on tourism websites. There is much information available for famous tourist destinations and little information for unknown tourist destinations. In particular, for foreign travelers, it is difficult to find their favorite tourist destinations, so we proposed a personal adaptive tourism recommendation system in former research. During the system development, the method of tourism feature extraction is a key issue. Via a questionnaire, we showed the importance of photo information on tourism websites. As the first step of the tourism feature extraction of photos on tourism websites, we propose two methods of analysis: color analysis and image recognition. Comparing the two methods through experiments, we confirmed that each method had different characteristics and the combination of these methods exhibited the best accuracy in distinguishing between the ratio of artificial and natural objects in the photos.


Keywords: Feature extraction, Tourism websites, Color analysis, Image recognition, Tourism recommendation system.


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ARTICLE INFORMATION


Received: 2021-03-05
Revised: 2021-04-12
Accepted: 2021-04-28
Available Online: 2021-09-01


Cite this article:

Li, S., Sasaki, J. 2021. Comparison of feature extraction methods by color analysis and image recognition for photos on tourism websites, International Journal of Applied Science and Engineering. 18, 2021083. https://doi.org/10.6703/IJASE.202109_18(5).002

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


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