Classification of a person picture and scenery picture using structured simplicity

초록

We can classify various images as either people pictures, if they contain one or more persons, or scenery pictures, if they lack people, by using face region detection. However, the precision of a picture's classification is low if it uses existing face region detection technique. This paper proposes the algorithm about structured simplicity of the picture to do classification with higher accuracy. To verify the usefulness of an offer method, we did a classification experiment which uses 500 people pictures and scenery pictures. The experiment to use only face region detection in Open CV showed an accuracy of 79% detection rate. While the experiment to use face region detection in structured simplicity with Open CV showed an accuracy of 86.4%. Therefore by using structured simplicity with face region detection, we can do an efficient picture classification of a person picture and scenery picture. © Springer-Verlag Berlin Heidelberg 2007.

제목
Classification of a person picture and scenery picture using structured simplicity
저자
Chung, M.-B.; Ko, I.-J.
발행일
2007
학회명
12th International Conference on Human-Computer Interaction, HCI International 2007
개최지
Beijing
학회 개최일
2007-07-22 ~ 2007-07-27