Abstract
This article presents a method aiming at filtering objectionable image contents. This kind of problem is very similar to object recognition and image classification. In this paper, we propose to use Adaptive-Subspace Self-Organizing Maps (ASSOM) to generate invariant pornographic features. To reach this goal, we construct local signatures associated to salient patches according to adult and benign databases. Then, we feed these vectors into each specialized ASSOM neural network. At the end of the learning step, each neural unit is tuned to a particular local signature prototype. Thus, each input image generates two neural maps that can be represented by two activation vectors. A supervised learning is finally done by a Normalized Radial Basis Function (NRBF) network to decide the image category. This scheme offers very promising results for image classification with a percentage of 87.8% of correct classification rates.
This work was carried out during the tenure of a MUSCLE Internal fellowship.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Forsyth, D.A., Fleck, M.M.: Identifying nude pictures. IEEE WACV 103–108 (1996)
Wang, J.Z., Li, J., Wiederhold, G., Firschein, O.: Classifying Objectionable Websites Based on Image Content. In: Plagemann, T., Goebel, V. (eds.) IDMS 1998. LNCS, vol. 1483, p. 113. Springer, Heidelberg (1998)
Jones, M.J., Rehg, J.M.: Statistical color models with application to skin detection. IJCV 46(1), 81–96 (2002)
Bosson, A., Cawley, G.C., Chan, Y., Harvey, R.: Non-retrieval: Blocking pornographic images. In: Lew, M., Sebe, N., Eakins, J.P. (eds.) CIVR 2002. LNCS, vol. 2383, pp. 50–60. Springer, Heidelberg (2002)
Zheng, H., Daoudi, M., Jedynak, B.: Blocking adult images based on statistical skin detection. ELCVIA 4(2), 1–14 (2004)
Kohonen, T.: Self-Organizing Maps. Springer, Heidelberg (2001)
Hoffman, J.E., Subramanium, B.: The role of visual attention in saccadic eye movements. Perception and Psychophysics 57, 787–795 (1995)
Tversky, A.: Features of similarity. Psychological Review 4(84), 327–352 (1977)
Duda, R.O., Stork, D.G., Hart, P.E.: Pattern Classification. Wiley Interscience, Chichester (2000)
Zhang, B., Fu, M., Yan, H., Jabri, M.A.: Handwritten digit recognition by adaptive-subspace self-organizing map (assom). IEEE Transactions on Neural Networks 4(10), 939–945 (1999)
Csurka, G., Dance, C., Fan, L., Willamowski, J., Bray, C.: Visual categorization with bags of keypoints. In: ECCV (2004)
Quelhas, P., Monay, F., Odobez, J.M., Gatica-Perez, D., Tuytelaars, T., Gool, L.V.: Modeling scenes with local descriptors and latent aspects. In: ICCV, pp. 883–890 (2005)
Laurent, C., Laurent, N., Maurizot, M., Dorval, T.: In depth analysis and evaluation of saliency-based color image indexing methods using wavelet salient features. Multimedia Tools and Application (2004)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proc. Fourth Alvey Vision Conf., pp. 147–151 (1988)
Bres, S., Jolion, J.M.: Detection of interest points for image indexation. In: 3rd Int. Conf. on Visual Information Systems, pp. 427–434 (1999)
Shapiro, J.: Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing 12(41), 3345–3462 (1993)
Geusebroek, J.M., Boomgrad, R., Smeulders, W.M., Geerts, H.: Color invariance. IEEE Transactions on PAMI 12(23), 1338–1350 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lefebvre, G., Zheng, H., Laurent, C. (2006). Objectionable Image Detection by ASSOM Competition. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_21
Download citation
DOI: https://doi.org/10.1007/11788034_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36018-6
Online ISBN: 978-3-540-36019-3
eBook Packages: Computer ScienceComputer Science (R0)