Active Shape Model-based Objectionable Image Detection


Seok-Woo Jang, Seong-Il Joo, Gye-Young Kim, Journal of Information Processing Systems Vol. 10, No. 5, pp. 183-194, Oct. 2009  


Keywords: Active Shape Model, Objectionable Images, Learning
Fulltext:

Abstract

In this paper, we propose a new method for detecting objectionable images with an active shape model. Our method first learns the shape of breast lines through principle component analysis and alignment as well as the distribution of intensity values of corresponding landmarks, and then extracts breast lines with the learned shape and intensity distribution. To accurately select the initial position of active shape model, we obtain parameters on scale, rotation, and translation. After positioning the initial location of active shape model using scale and rotation information, iterative searches are performed. We can identify adult images by calculating the average of the distance between each landmark and a candidate breast line. The experiment results show that the proposed method can detect adult images effectively by comparing various results.


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Cite this article
[APA Style]
Jang, S., Joo, S., & Kim, G. (2009). Active Shape Model-based Objectionable Image Detection. Journal of Internet Computing and Services, 10(5), 183-194.

[IEEE Style]
S. Jang, S. Joo, G. Kim, "Active Shape Model-based Objectionable Image Detection," Journal of Internet Computing and Services, vol. 10, no. 5, pp. 183-194, 2009.

[ACM Style]
Seok-Woo Jang, Seong-Il Joo, and Gye-Young Kim. 2009. Active Shape Model-based Objectionable Image Detection. Journal of Internet Computing and Services, 10, 5, (2009), 183-194.