Neural network used in Energy Function of Content-aware Image Resizing Method to Preserve Skin Color Region
Seam Carving is a content-aware image resizing method capable of modifying the width or height of pictures. Such an algorithm applies an energy function to evaluate the importance of each pixel in the image. In exceptional cases, such as images that contain people, the method frequently presents deformation of objects due to the energy function not being able to detect a person. In this context, this paper presents a modification of the energy function used in seam carving by employing a neural network which can detect human skin patterns. Such a modification aims at better-preserving people in images. The experiments show that the proposed method achieves superior performance in terms of visual quality through qualitative indexes compared to the original algorithm.
Baskan, S., Bulut, M. M., & Atalay, V. (2002). Projection based method for segmentation of human face and its evaluation. Pattern Recognition Letters, 23(14):1623–1629.
Bhute, A. N. & Meshram, B. (2014). Content based image indexing and retrieval. arXiv preprint arXiv:1401.1742.
Casati, J. P. B., Moraes, D. R., & Rodrigues, E. L. L. (2013). Sfa: A human skin image database based on feret and ar facial images. In IX workshop de Visao Computational, Rio de Janeiro.
Dong, W., Zhou, N., Paul, J.-C., & Zhang, X. (2009). Optimized image resizing using seam carving and scaling. In ACM Transactions on Graphics (TOG), volume 28, page 125. ACM.
Fang, Y., Chen, Z., Lin, W., & Lin, C.-W. (2012). Saliency detection in the compressed domain for adaptive image retargeting. IEEE Transactions on Image Processing, 21(9):3888–3901.
Fang, Y., Zeng, K., Wang, Z., Lin, W., Fang, Z., & Lin, C.-W. (2014). Objective quality assessment for image retargeting based on structural similarity. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 4(1):95–105.
Habili, N., Lim, C. C., & Moini, A. (2004). Segmentation of the face and hands in sign language video sequences using color and motion cues. IEEE Transactions on Circuits and Systems for Video Technology, 14(8):1086–1097.
Hajiarbabi, M. & Agah, A. (2015). Human skin color detection using neural networks. Journal of Intelligent Systems, 24(4):425–436.
Han, J., Awad, G., & Sutherland, A. (2009). Automatic skin segmentation and tracking in sign language recognition. IET Computer Vision, 3(1):24–35.
Kakumanu, P., Makrogiannis, S., & Bourbakis, N. (2007). A survey of skin-color modeling and detection methods. Pattern recognition, 40(3):1106–1122.
Kang, S., Choi, B., & Jo, D. (2016). Faces detection method based on skin color modeling. Journal of Systems Architecture, 64:100–109.
Liu, C., Yuen, J., & Torralba, A. (2011). Sift flow: Dense correspondence across scenes and its applications. IEEE transactions on pattern analysis and machine intelligence, 33(5):978–994.
Liu, C.-C. & Chung, P.-C. (2011). Objects extraction algorithm of color image using adaptive forecasting filters created automatically. International Journal of Innovative Computing, Information and Control, 7(10):5771–5787.
M. Martinez, A. & Benavente, R. (1998). The ar face database. Tech. Rep. 24 CVC Technical Report.
Moallem, P., Mousavi, B. S., & Monadjemi, S. A. (2011). A novel fuzzy rule base system for pose independent faces detection. Applied Soft Computing, 11(2):1801–1810.
Naji, S., Jalab, H. A., & Kareem, S. A. (2018). A survey on skin detection in colored images. Artificial Intelligence Review.
Naji, S. A. (2013). Human face detection from colour images based on multi-skin models, rule-based geometrical knowledge, and artificial neural network. PhD thesis, University of Malaya.
Nguyen, D. T., Li, W., & Ogunbona, P. O. (2016). Human detection from images and videos: A survey. Pattern Recognition, 51:148–175.
Oliveira, S. A., Bezerra, F. N., & Neto, A. R. R. (2015). Genetic seam carving: A genetic algorithm approach for content-aware image retargeting. In Iberian Conference on Pattern Recognition and Image Analysis, pages 700–707. Springer.
Perez, M., Avila, S., Moreira, D., Moraes, D., Testoni, V., Valle, E., Goldenstein, S., & Rocha, A. (2017). Video pornography detection through deep learning techniques and motion information. Neurocomputing, 230:279–293.
Phillips, P. J., Wechsler, H., Huang, J., & Rauss, P. J. (1998). The feret database and evaluation procedure for face-recognition algorithms. Image and vision computing, 16(5):295–306.
Phung, S. L., Bouzerdoum, A., & Chai, D. (2003). Skin segmentation using color and edge information. In Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., volume 1, pages 525–528. IEEE.
Rubinstein, M., Gutierrez, D., Sorkine, O., & Shamir, A. (2010). A comparative study of image retargeting. ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 29(6):160:1–160:10.
Rubinstein, M., Shamir, A., & Avidan, S. (2009). Multi-operator media retargeting. ACM Transactions on graphics (TOG), 28(3):23.
Rumelhart, D. E., Hinton, G. E., Williams, R. J., et al. (1988). Learning representations by back-propagating errors. Cognitive modeling, 5(3):1.
Samadani, R., Lim, S. H., & Tretter, D. (2007). Representative image thumbnails for good browsing. In 2007 IEEE International Conference on Image Processing, volume 2, pages II–193. IEEE.
Senturk, Z. K. & Akgun, D. (2017). Seam carving based image resizing detection using hybrid features. Tehnicki Vjesnik-Technical Gazette, 24(6):1825–1833.
Shamir, A. & Avidan, S. (2009). Seam carving for media retargeting. Communications of the ACM, 52(1):77–85.
Wolf, L., Guttmann, M., & Cohen-Or, D. (2007). Non-homogeneous content-driven video-retargeting. In 2007 IEEE 11th International Conference on Computer Vision, pages 1–6. IEEE.
Yuetao, D. & Nana, Y. (2011). Research of face detection in color image based on skin color. Energy Procedia, 13:9395–9401.
Zhipeng, C., Junda, H., & Wenbin, Z. (2010). Face detection system based on skin color model. In 2010 International Conference on Networking and Digital Society, volume 2, pages 664–667. IEEE.