{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T14:53:37Z","timestamp":1768316017866,"version":"3.49.0"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"28-29","license":[{"start":{"date-parts":[[2020,6,12]],"date-time":"2020-06-12T00:00:00Z","timestamp":1591920000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,6,12]],"date-time":"2020-06-12T00:00:00Z","timestamp":1591920000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A cosmetic product recognition system is proposed in this paper. For this recognition system, we have proposed a cosmetic product database that contains image samples of forty different cosmetic items. The purpose of this recognition system is to recognize Cosmetic products with there types, brands and retailers such that to analyze a customer experience what kind of products and brands they need. This system has various applications in such as brand recognition, product recognition and also the availability of the products to the vendors. The implementation of the proposed system is divided into three components: preprocessing, feature extraction and classification. During preprocessing we have scaled and transformed the color images into gray-scaled images to speed up the process. During feature extraction, several different feature representation schemes: transformed, structural and statistical texture analysis approaches have been employed and investigated by employing the global and local feature representation schemes. Various machine learning supervised classification methods such as Logistic Regression, Linear Support Vector Machine, Adaptive k-Nearest Neighbor, Artificial Neural Network and Decision Tree classifiers have been employed to perform the classification tasks. Apart from this, we have also performed some data analytic tasks for Brand Recognition as well as Retailer Recognition and for these experimentation, we have employed some datasets from the \u2018Kaggle\u2019 website and have obtained the performance due to the above-mentioned classifiers. Finally, the performance of the cosmetic product recognition system, Brand Recognition and Retailer Recognition have been aggregated for the customer decision process in the form of the state-of-the-art for the proposed system.<\/jats:p>","DOI":"10.1007\/s11042-020-09079-y","type":"journal-article","created":{"date-parts":[[2020,6,12]],"date-time":"2020-06-12T07:02:42Z","timestamp":1591945362000},"page":"34997-35023","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Machine learning method for cosmetic product recognition: a visual searching approach"],"prefix":"10.1007","volume":"80","author":[{"given":"Saiyed","family":"Umer","sequence":"first","affiliation":[]},{"given":"Partha Pratim","family":"Mohanta","sequence":"additional","affiliation":[]},{"given":"Ranjeet Kumar","family":"Rout","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9128-068X","authenticated-orcid":false,"given":"Hari Mohan","family":"Pandey","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,6,12]]},"reference":[{"key":"9079_CR1","unstructured":"(2012) Retail Data Analytics. https:\/\/www.kaggle.com\/manjeetsingh\/retaildataset"},{"key":"9079_CR2","unstructured":"(2019) eCommerce Events History in Cosmetics Shop Dataset. https:\/\/www.kaggle.com\/mkechinov\/cosmetics-ecommerce-data-overview\/data"},{"issue":"1","key":"9079_CR3","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/T-C.1974.223784","volume":"100","author":"Nasir Ahmed","year":"1974","unstructured":"Ahmed Nasir, Natarajan T, Rao KR (1974) Discrete cosine transform. IEEE transactions on Computers 100(1):90\u201393","journal-title":"IEEE transactions on Computers"},{"key":"9079_CR4","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.patrec.2016.08.016","volume":"84","author":"V Andrearczyk","year":"2016","unstructured":"Andrearczyk V, Whelan P F (2016) Using filter banks in convolutional neural networks for texture classification. Pattern Recogn Lett 84:63\u201369","journal-title":"Pattern Recogn Lett"},{"issue":"8","key":"9079_CR5","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1109\/34.531803","volume":"18","author":"SM Bangalore","year":"1996","unstructured":"Bangalore SM, Ma W-Y (1996) Texture features for browsing and retrieval of image data. IEEE Transactions on pattern analysis and machine intelligence 18 (8):837\u2013842","journal-title":"IEEE Transactions on pattern analysis and machine intelligence"},{"key":"9079_CR6","unstructured":"Bhabatosh C, et al. (2011) Digital image processing and analysis. PHI Learning Pvt Ltd."},{"key":"9079_CR7","doi-asserted-by":"crossref","unstructured":"Chan J, Lee JA, Kemao Q (2017) Bind: Binary integrated net descriptors for texture-less object recognition. In: Proc. CVPR","DOI":"10.1109\/CVPR.2017.322"},{"issue":"3","key":"9079_CR8","first-page":"27","volume":"2","author":"C-C Chang","year":"2011","unstructured":"Chang C-C, Lin C-J (2011) Libsvm: a library for support vector machines. ACM transactions on intelligent systems and technology (TIST) 2(3):27","journal-title":"ACM transactions on intelligent systems and technology (TIST)"},{"key":"9079_CR9","doi-asserted-by":"crossref","unstructured":"Costa AF, Humpire-Mamani G, Traina Agma JM (2012) An efficient algorithm for fractal analysis of textures. In: Graphics, Patterns and Images (SIBGRAPI), 2012 25th SIBGRAPI Conference on, pages 39\u201346. IEEE","DOI":"10.1109\/SIBGRAPI.2012.15"},{"key":"9079_CR10","unstructured":"Dalal N (2005) Bill Triggs. Histograms of oriented gradients for human detection. In: Computer Vision and Pattern Recognition, 2005. CVPR IEEE Computer Society Conference on, volume 1, pages 886\u2013893, IEEE, 2005"},{"issue":"12","key":"9079_CR11","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1145\/2500499","volume":"56","author":"V Dhar","year":"2013","unstructured":"Dhar V (2013) Data science and prediction. Commun ACM 56(12):64\u201373","journal-title":"Commun ACM"},{"key":"9079_CR12","unstructured":"Ethem A (2010) Introduction to machine learning sl"},{"issue":"1","key":"9079_CR13","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1023\/B:VISI.0000042934.15159.49","volume":"61","author":"PF Felzenszwalb","year":"2005","unstructured":"Felzenszwalb PF, Huttenlocher Daniel P (2005) Pictorial structures for object recognition. International journal of computer vision 61(1):55\u201379","journal-title":"International journal of computer vision"},{"issue":"3","key":"9079_CR14","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/s11263-006-8707-x","volume":"71","author":"R Fergus","year":"2007","unstructured":"Fergus R, Perona P, Zisserman A (2007) Weakly supervised scale-invariant learning of models for visual recognition. International journal of computer vision 71 (3):273\u2013303","journal-title":"International journal of computer vision"},{"key":"9079_CR15","unstructured":"Forsyth DA, Ponce J (2002) Computer vision: a modern approach Prentice Hall Professional Technical Reference"},{"key":"9079_CR16","first-page":"296","volume":"12","author":"WT Freeman","year":"1995","unstructured":"Freeman WT, Roth M (1995) Orientation histograms for hand gesture recognition. In International workshop on automatic face and gesture recognition 12:296\u2013301","journal-title":"In International workshop on automatic face and gesture recognition"},{"key":"9079_CR17","doi-asserted-by":"crossref","unstructured":"Gehler P, Nowozin S (2009) On feature combination for multiclass object classification. In: Computer Vision IEEE 12th International Conference on, pages 221\u2013228, IEEE, 2009","DOI":"10.1109\/ICCV.2009.5459169"},{"key":"9079_CR18","unstructured":"Gonzalez RC, Woods RE (2002) Digital image processing second edition Beijing: Publishing house of electronics industry 455"},{"issue":"1-2","key":"9079_CR19","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/S0925-5273(01)00191-8","volume":"75","author":"A Gunasekaran","year":"2002","unstructured":"Gunasekaran A, Marri HB, Mcgaughey RE, Nebhwani MD (2002) E-commerce and its impact on operations management. International journal of production economics 75(1-2):185\u2013197","journal-title":"International journal of production economics"},{"key":"9079_CR20","doi-asserted-by":"crossref","unstructured":"Guyon I, Elisseeff A (2006) An introduction to feature extraction. In: Feature extraction, pages 1\u201325. Springer","DOI":"10.1007\/978-3-540-35488-8_1"},{"issue":"4","key":"9079_CR21","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1109\/TGRS.1990.572934","volume":"28","author":"D-C He","year":"1990","unstructured":"He D-C, Li W (1990) Texture unit, texture spectrum, and texture analysis. IEEE transactions on Geoscience and Remote Sensing 28(4):509\u2013512","journal-title":"IEEE transactions on Geoscience and Remote Sensing"},{"key":"9079_CR22","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"1","key":"9079_CR23","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1109\/MC.2003.1160055","volume":"36","author":"JO Kephart","year":"2003","unstructured":"Kephart JO, Chess DM (2003) The vision of autonomic computing. Computer 36(1):41\u201350","journal-title":"Computer"},{"key":"9079_CR24","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097\u20131105"},{"issue":"11","key":"9079_CR25","doi-asserted-by":"publisher","first-page":"1572","DOI":"10.1109\/83.799885","volume":"8","author":"M Lance","year":"1999","unstructured":"Lance M (1999) Kaplan. Extended fractal analysis for texture classification and segmentation. IEEE Trans Image Process 8(11):1572\u20131585","journal-title":"IEEE Trans Image Process"},{"key":"9079_CR26","unstructured":"LeCun Y et al (2015) Lenet-5, convolutional neural networks. http:\/\/yann.lecun.com\/exdb\/lenet, page 20"},{"key":"9079_CR27","doi-asserted-by":"crossref","unstructured":"Liang M, Xiaolin Hu (2015) Recurrent convolutional neural network for object recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 3367\u2013 3375","DOI":"10.1109\/CVPR.2015.7298958"},{"key":"9079_CR28","doi-asserted-by":"crossref","unstructured":"Lowe DG (1999) Object recognition from local scale-invariant features. In: Computer vision, 1999. The proceedings of the seventh IEEE international conference on, volume 2, pages 1150\u20131157. Ieee","DOI":"10.1109\/ICCV.1999.790410"},{"key":"9079_CR29","unstructured":"Lowe DG (2004) Method, apparatus for identifying scale invariant features in an image and use of same for locating an object in an image, March 23 US Patent 6,711,293"},{"issue":"10","key":"9079_CR30","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1016\/j.imavis.2004.02.006","volume":"22","author":"J Matas","year":"2004","unstructured":"Matas J, Chum O, Urban M, Pajdla T (2004) Robust wide-baseline stereo from maximally stable extremal regions. Image and vision computing 22(10):761\u2013767","journal-title":"Image and vision computing"},{"key":"9079_CR31","unstructured":"McConnell RK (1986) Method of and apparatus for pattern recognition, January 28. US Patent 4,567,610"},{"key":"9079_CR32","unstructured":"Michalski RS, Carbonell J G, Mitchell TM (2013) Machine learning: An artificial intelligence approach Springer Science & Business Media"},{"key":"9079_CR33","doi-asserted-by":"crossref","unstructured":"Mullick SS, Datta S, Das S (2018) Adaptive learning-based k-nearest neighbor classifiers with resilience to class imbalance IEEE Transactions on Neural Networks and Learning Systems","DOI":"10.1109\/TNNLS.2018.2812279"},{"issue":"4","key":"9079_CR34","doi-asserted-by":"publisher","first-page":"049901","DOI":"10.1117\/1.2819119","volume":"16","author":"NM Nasrabadi","year":"2007","unstructured":"Nasrabadi N M (2007) Pattern recognition and machine learning. Journal of electronic imaging 16(4):049901","journal-title":"Journal of electronic imaging"},{"key":"9079_CR35","doi-asserted-by":"crossref","unstructured":"Nowak E, Jurie F, Triggs B (2006) Sampling strategies for bag-of-features image classification. In: European conference on computer vision, pages 490\u2013503. Springer","DOI":"10.1007\/11744085_38"},{"key":"9079_CR36","doi-asserted-by":"crossref","unstructured":"Obdr\u017e\u00e1lek \u0160, Matas J (2006) Object recognition using local affine frames on maximally stable extremal regions. In: Toward Category-Level Object Recognition, pages 83\u2013104. Springer","DOI":"10.1007\/11957959_5"},{"key":"9079_CR37","unstructured":"Ojala T, Pietikainen M, Harwood D (1994) Performance evaluation of texture measures with classification based on kullback discrimination of distributions. In: Pattern Recognition Vol. 1-Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on, volume 1, pages 582\u2013585, IEEE, 1994"},{"issue":"7","key":"9079_CR38","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","volume":"24","author":"T Ojala","year":"2002","unstructured":"Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on pattern analysis and machine intelligence 24(7):971\u2013987","journal-title":"IEEE Transactions on pattern analysis and machine intelligence"},{"key":"9079_CR39","doi-asserted-by":"crossref","unstructured":"Oluleye HB, Armstrong L, Leng J, Diepeveen D (2014) Zernike moments and genetic algorithm. Tutorial and application","DOI":"10.9734\/BJMCS\/2014\/10931"},{"key":"9079_CR40","doi-asserted-by":"crossref","unstructured":"Ouyang W, Wang X, Zeng X, Qiu S, Luo P, Tian Y, Li H, Yang S, Wang Z, Loy C-C, et al. (2015) Deepid-net: Deformable deep convolutional neural networks for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 2403\u20132412","DOI":"10.1109\/CVPR.2015.7298854"},{"issue":"8","key":"9079_CR41","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/j.imavis.2012.06.004","volume":"30","author":"P Piccinini","year":"2012","unstructured":"Piccinini P, Prati A, Cucchiara R (2012) Real-time object detection and localization with sift-based clustering. Image Vis Comput 30(8):573\u2013587","journal-title":"Image Vis Comput"},{"key":"9079_CR42","doi-asserted-by":"crossref","unstructured":"Ponce J, Hebert M, Schmid C, Zisserman A (2007) Toward category-level object recognition, volume 4170 Springer","DOI":"10.1007\/11957959"},{"key":"9079_CR43","doi-asserted-by":"crossref","unstructured":"Porter SS, Claycomb C (1997) The influence of brand recognition on retail store image Journal of product & brand management","DOI":"10.1108\/10610429710190414"},{"key":"9079_CR44","doi-asserted-by":"crossref","unstructured":"Ramsay J-O (2004) Functional data analysis. Encyclopedia of Statistical Sciences, pp 4","DOI":"10.1002\/0471667196.ess0646"},{"key":"9079_CR45","unstructured":"Raschka S (2015) Python machine learning Packt Publishing Ltd"},{"issue":"3","key":"9079_CR46","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/s11263-005-3674-1","volume":"66","author":"Fred Rothganger","year":"2006","unstructured":"Rothganger Fred, Lazebnik Svetlana, Schmid C, Ponce J (2006) 3d object modeling and recognition using local affine-invariant image descriptors and multi-view spatial constraints. Int J Comput Vis 66(3):231\u2013259","journal-title":"Int J Comput Vis"},{"key":"9079_CR47","doi-asserted-by":"crossref","unstructured":"Sachs A-L, et al. (2015) Retail analytics Lecture Notes in Economics and Mathematical Systems","DOI":"10.1007\/978-3-319-13305-8"},{"issue":"3","key":"9079_CR48","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1109\/21.97458","volume":"21","author":"RS Safavian","year":"1991","unstructured":"Safavian RS, Landgrebe D (1991) A survey of decision tree classifier methodology. IEEE transactions on systems, man, and cybernetics 21(3):660\u2013674","journal-title":"IEEE transactions on systems, man, and cybernetics"},{"key":"9079_CR49","doi-asserted-by":"crossref","unstructured":"Saravanan C (2010) Color image to grayscale image conversion. In: Computer Engineering and Applications (ICCEA), 2010 Second International Conference on, volume 2, pages 196\u2013199. IEEE","DOI":"10.1109\/ICCEA.2010.192"},{"key":"9079_CR50","first-page":"944,357","volume":"11","author":"Sheldon G","year":"2008","unstructured":"Sheldon G (2008) Analytical e-commerce processing system and methods, July 3. US Patent App. 11:944,357","journal-title":"US Patent App."},{"key":"9079_CR51","doi-asserted-by":"crossref","unstructured":"Shih Y-F, Yeh Y-M, Lin Y-Y, Weng M-F, Lu Y-C, Chuang Y-Y (2017) Deep co-occurrence feature learning for visual object recognition. In: Proc. Conf. Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2017.772"},{"key":"9079_CR52","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556"},{"key":"9079_CR53","doi-asserted-by":"crossref","unstructured":"Sivic J, Russell BC, Zisserman A, Freeman William T, Efros AA (2008) Unsupervised discovery of visual object class hierarchies. In: Computer Vision and Pattern Recognition, 2008. CVPR IEEE Conference on, pages 1\u20138. IEEE, 2008","DOI":"10.1109\/CVPR.2008.4587622"},{"issue":"4","key":"9079_CR54","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1109\/TPAMI.2008.111","volume":"31","author":"J Sivic","year":"2009","unstructured":"Sivic J, Zisserman A (2009) Efficient visual search of videos cast as text retrieval. IEEE transactions on pattern analysis and machine intelligence 31(4):591\u2013606","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"9079_CR55","doi-asserted-by":"crossref","unstructured":"Szeliski R (2010) Computer vision: algorithms and applications Springer Science & Business Media","DOI":"10.1007\/978-1-84882-935-0"},{"issue":"11","key":"9079_CR56","doi-asserted-by":"publisher","first-page":"1602","DOI":"10.1109\/83.725367","volume":"7","author":"X Tang","year":"1998","unstructured":"Tang X (1998) Texture information in run-length matrices. IEEE transactions on image processing 7(11):1602\u20131609","journal-title":"IEEE transactions on image processing"},{"issue":"1","key":"9079_CR57","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1109\/TGRS.2014.2321423","volume":"53","author":"P Tokarczyk","year":"2015","unstructured":"Tokarczyk P, Wegner JD, Walk S, Schindler K (2015) Features, color spaces, and boosting: New insights on semantic classification of remote sensing images. IEEE Transactions on Geoscience and Remote Sensing 53(1):280\u2013295","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"2","key":"9079_CR58","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1080\/02564602.2016.1265904","volume":"35","author":"S Umer","year":"2018","unstructured":"Umer S, Dhara BC, Chanda B (2018) An iris recognition system based on analysis of textural edgeness descriptors. IETE Technical Review 35(2):145\u2013156","journal-title":"IETE Technical Review"},{"key":"9079_CR59","doi-asserted-by":"crossref","unstructured":"Van de Wouwer G, Scheunders P, Van Dyck D (1999) Statistical texture characterization from discrete wavelet representations. IEEE transactions on image processing 8(4):592\u2013598","DOI":"10.1109\/83.753747"},{"key":"9079_CR60","doi-asserted-by":"crossref","unstructured":"Wang S (2011) A review of gradient-based and edge-based feature extraction methods for object detection. In: Computer and Information Technology (CIT), 2011 IEEE 11Th International Conference on, pages 277\u2013282. IEEE, 2011","DOI":"10.1109\/CIT.2011.51"},{"key":"9079_CR61","doi-asserted-by":"crossref","unstructured":"Wu C-C, Zeng Y-C, Shih M-J (2015) Enhancing retailer marketing with an facial recognition integrated recommender system. In: 2015 IEEE International Conference on Consumer Electronics-Taiwan, pages 25\u201326. IEEE","DOI":"10.1109\/ICCE-TW.2015.7216881"},{"key":"9079_CR62","doi-asserted-by":"crossref","unstructured":"Xu Z, Zhu L, Yang Y (2017) Few-shot object recognition from machine-labeled web images. In: Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR.2017.569"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09079-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09079-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09079-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T08:27:20Z","timestamp":1696235240000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09079-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,12]]},"references-count":62,"journal-issue":{"issue":"28-29","published-print":{"date-parts":[[2021,11]]}},"alternative-id":["9079"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09079-y","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,12]]},"assertion":[{"value":"11 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 April 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 June 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}