Abstract
In this paper we present a modified Bag-of-Words algorithm used in image classification. The classic Bag-of-Words algorithm is used in natural language processing. A text (such as a sentence or a document) is represented as a bag of words. In image retrieval or image classification this algorithm also works on one characteristic image feature and most often it is a descriptor defining the surrounding of a keypoint obtained by using e.g. the SURF algorithm. The modification which we have introduced involves using two different types of image features – the descriptor of a keypoint and also the colour histogram, which can be obtained from the surrounding of a keypoint. This additional feature will make it possible to obtain more information as the commonly used SURF algorithm works only on images with greyscale intensity. The experiments which we have conducted show that using this additional image feature significantly improves image classification results by using the BoW algorithm.
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References
Audet, S.: JavaCV (2017). http://bytedeco.org/. Accessed 1 Feb 2017
Bay, H., Tuytelaars, T., Gool, L.: SURF: Speeded Up Robust Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006). doi:10.1007/11744023_32
Bertini Junior, J.R., Nicoletti, M.C.: Enhancing constructive neural network performance using functionally expanded input data. J. Artif. Intell. Soft Computing Res. 6(2), 119–131 (2016)
Bilski, J., Wilamowski, B.M.: Parallel learning of feedforward neural networks without error backpropagation. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS, vol. 9692, pp. 57–69. Springer, Cham (2016). doi:10.1007/978-3-319-39378-0_6
Bradski, G.: The OpenCV Library. Dr. Dobb’s Journal of Software Tools (2000)
Christina, B., Eugene, S., Maxim, S.: Multi-objective heuristic feature selection for speech-based multilingual emotion recognition. J. Artif. Intell. Soft Comput. Res. 6(4), 243 (2016)
Csurka, G., Dance, C.R., Fan, L., Willamowski, J., Bray, C.: Visual categorization with bags of keypoints. In: Workshop on Statistical Learning in Computer Vision, ECCV, pp. 1–22 (2004)
Dittenbach, M., Merkl, D., Rauber, A.: The growing hierarchical self-organizing map. In: Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, vol. 6, pp. 15–19 (2000)
Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories. In: Conference on Computer Vision and Pattern Recognition Workshop, CVPRW 2004, pp. 178–178 (2004)
Kasthurirathna, D., Piraveenan, M., Uddin, S.: Evolutionary stable strategies in networked games: the influence of topology. J. Artif. Intell. Soft Comput. Res. 5(2), 83–95 (2015)
Korytkowski, M.: Novel visual information indexing in relational databases. Integr. Comput.-Aid. Eng. 24(2), 119–128 (2017)
Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2169–2178 (2006)
Li, F.F., Perona, P.: A Bayesian hierarchical model for learning natural scene categories. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 2, pp. 524–531. IEEE Computer Society (2005)
Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Moulin, C., Barat, C., Ducottet, C.: Fusion of tf.idf weighted bag of visual features for image classification. In: 2010 International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 1–6 (2010)
Sivic, J., Russell, B., Efros, A., Zisserman, A., Freeman, W.: Discovering objects and their location in images. In: Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 1, pp. 370–377 (2005)
Starczewski, A., Krzyżak, A.: A modification of the Silhouette index for the improvement of cluster validity assessment. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS, vol. 9693, pp. 114–124. Springer, Cham (2016). doi:10.1007/978-3-319-39384-1_10
Starczewski, J.: Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty, Studies in Fuzziness and Soft Computing, vol. 284. Springer, Heidelberg (2013)
Staszewski, P., Woldan, P., Korytkowski, M., Scherer, R., Wang, L.: Query-by-example image retrieval in microsoft SQL server. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS, vol. 9693, pp. 746–754. Springer, Cham (2016). doi:10.1007/978-3-319-39384-1_66
Woźniak, M.: Novel image correction method based on swarm intelligence approach. In: Dregvaite, G., Damasevicius, R. (eds.) ICIST 2016. CCIS, vol. 639, pp. 404–413. Springer, Cham (2016). doi:10.1007/978-3-319-46254-7_32
Wozniak, M., Polap, D.: On manipulation of initial population search space in heuristic algorithm through the use of parallel processing approach. In: 2016 IEEE Symposium Series on Computational Intelligence, pp. 1–6. IEEE (2016)
Wozniak, M., Polap, D., Napoli, C., Tramontana, E.: Graphic object feature extraction system based on cuckoo search algorithm. Expert Syst. Appl. 66, 20–31 (2016)
Zalasiński, M., Cpałka, K.: New algorithm for on-line signature verification using characteristic hybrid partitions. In: Wilimowska, Z., Borzemski, L., Grzech, A., Świątek, J. (eds.) ISAT 2015. AISC, vol. 432, pp. 147–157. Springer, Cham (2016). doi:10.1007/978-3-319-28567-2_13
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Gabryel, M., Damaševičius, R. (2017). The Image Classification with Different Types of Image Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_44
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