Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE. 35253528 IEEE,IEEE Signal Processing SocietyLowe, D., Distinctive image features from scale-invariant keypoints (2004) IJCV, 60 (2), pp. 91-110. , FebruaryMikolajczyk, K., Schmid, C., Scale & affine invariant interest point detectors (2004) IJCV, 60 (1), pp. 63-86Demirci, M.F., Shokoufandeh, A., Keselman, Y., Bretzner, L., Dickinson, S., Object recognition as many-to-many feature matching (2006) International Journal of Computer Vision, 69 (2), pp. 203-222. , DOI 10.1007/s11263-006-6993-yStoettinger, J., Hanbury, A., Sebe, N., Gevers, T., Do colour interest points improve image retrieval (2007) ICIP, pp. 169-172Valle, E., (2008) Local-descriptor Matching for Image Identification Systems, , Phd thesis, Universit de Cergy-Pontoise, Cergy-Pontoise, FranceSivic, J., Zisserman, A., Video google: A text retrieval approach to object matching in videos (2003) IEEE ICCV, pp. 1470-1477Papa, J.P., Falcão, A.X., Suzuki, C.T.N., Supervised pattern classification based on optimum-path forest (2009) IJIST, 19 (2), pp. 120-131Winn, J., Criminisi, A., Minka, T., Object categorization by learned universal visual dictionary (2005) IEEE ICCV, pp. 1800-1807Ulusoy, I., Bishop, C.M., Generative versus discriminative methods for object recognition (2005) IEEE CVPR, 2Csurka, G., Dance, C.R., Fan, L., Willamowski, J., Bray, C., Visual categorization with bags of keypoints Workshop on Statistical Learning in Computer Vision, 2004Bay, H., Tuytelaars, T., Van Gool, L., SURF: Speeded up robust features European Conference on Computer Vision, 2006, pp. 1-14Bishop, C.M., (2006) Pattern Recognition and Machine Learning, , Springer, 1 edition