A comparison of SIFT, PCA-SIFT and SURF

This paper compares three robust feature detection methods, they are, Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA) -SIFT and Speeded Up Robust Features (SURF). Lowe presented SIFT [1], which was successfully used in recognition, stitching and many other applications because of its robustness. Yan Ke [2] gave a change of SIFT by using PCA to normalize the gradient patch instead of histogram. H. Bay [3] presented a faster method for SURF, which used Fast-Hessian detector. The performance of the three methods is compared for scale changes, rotation , blur, illumination changes and affine transformations, all of which uses repeatability as an evaluation measurement. Additionally, RANSAC is used to reject the inconsistent matches [4]. SIFT presents its stability in most situation except rotation and illumination changes. SURF is the fastest one with good performance as the same as SIFT, PCASIFT shows its advantages in rotation, blur and illumination changes. CITED BY (442) 1 Han, C. H. (2010). Reduced Dimensional SURF Based Hand Gesture Recognition. 2 Su, C. R. (2014). Unsupervised Image Segmentation by Dual Morphological Operations and Peer-toPeer Content-Based Image Retrieval Applications (Doctoral dissertation). 3 Hu, H. H. (2013). Smartphone Positioning with Street View Image Database. 4 Fl�rez Revuelta, F., & Chaaraoui, A. A. (2012). Interfaz de control dom�tico basada en un sistema de detecci�n de postura. 5 Idrobo Pizo, G. A. (2014). Projeto de um descritor para o alinhamento de imagens de profundidade de superf�cies com aplica��o em vis�o rob�tica. 6 Einrichtung, B., & f�r Lehrerbildung, Z. OPUS-Passau. 7 Rhee, S. B. (2013). Efficient Image Stitching Using Fast Feature Descriptor Extraction and Matching. KIPS Transactions on Software and Data Engineering, 2(1), 65-70. 8 de Souza Tarallo, A., da Silva, F. A., Hiraga, A. K., de Paiva, M. S. V., & de Castro Jorge, L. A. Mosaicos de Imagens A�reas Sequenciais Constru�dos Automaticamente. 9 Valenzuela, R. E., Schwartz, W. R., & Pedrini, H. Redu��o de Dimensionalidade Aplicada � Descri��o de Caracter�sticas Visuais. 10 COMIT�, Y. A. P. E. S. Eduardo Quintana Contreras. 11 Augereau, O. (2013). Reconnaissance et classification d'images de documents (Doctoral dissertation, Universit� Sciences et Technologies-Bordeaux I). 12 de Souza Tarallo, A., Hiraga, A. K., Martinez, G. A. G., de Paiva, M. S. V., de Castro Jorge, L. A., & Senger, H. Uso de mosaico de imagens a�reas como ferramenta de aux�lio ao diagn�stico de diversas culturas*. 13 GALLA, H. Z. (2015). PENGELOMPOKAN CITRA RAMBU LALU LINTAS DENGAN HIERARCHICAL AGGLOMERATIVE CLUSTERING BERBASIS SCALE INVARIANT FEATURE TRANSFORM. Skripsi, Fakultas Ilmu Komputer. MANUSCRIPT AUTHORS Miss Luo Juan Korea South qiuhehappy@hotmail.com Dr. Oubong Gwun Computer Graphics Lab, Chonbuk National University, Jeonju 561-756, South Korea South Korea A comparison of sift, pca-sift and surf 14 Renkens, I. M. (2015). Prometheus: from 2D to 3D. A reconstruction based on photographs (Doctoral dissertation, TU Delft, Delft University of Technology). 15 CIOU, J. J. (2014). Embedded Omni-Directional Wheeled Mobile Robot Visual SLAM based on Depth Image Database. 16 Prieto S�nchez, J. (2011). Reconocimiento de objetos por visi�n artificial en entornos controlados. 17 Campos, M. F. M. 2� Lista de Exerc�cios 1 Exerc�cios Te�ricos. 18 Liedtke, A. Realisierung eines robusten Verfahrens zur Identifikation von Positionsmarken unter Verwendung von Bildverarbeitung in Videobildern. 19 Quintana Rosales, M. A. (2015). Registro de una secuencia temporal de nubes de puntos utilizando tecnolog�a Kinect para la reconstrucci�n tridimensional de material arqueol�gico. 20 Mauricio, C. J. L., Edgar, F. S., & Samuel, R. H. E. (2012). Sistema M�vil de Virtualizaci�n, Edici�n y Visualizaci�n de Objetos 3D (VIAR). 21 de Souza Tarallo, A. (2013). Escola de Engenharia de S�o Carlos (Doctoral dissertation, Universidade de S�o Paulo). 22 BOUACHIR, W., & DOCTOR, O. D. D. D. P. (2014). SUIVI D�OBJETS PAR CARACT�RISTIQUES LOCALES ENCODANT LA STRUCTURE. 23 Hung, C. Y. (2014). Reasearch and Validation of Application of Adaptive Template Building Technology to Lithography Pattern of Light Emitting Diode Chip. 24 Jatmiko, S. Analisis Dan Implementasi Penggunaan Scale Invariant Feature Transform (SIFT) Pada Sistem Verifikasi Tanda Tangan. 25 Pizarro, C. A. (2014). On the possibility to find coordinates by random features (Doctoral dissertation, Autonomous University of Madrid). 26 Creve, M. Navigatiehulp voor mensen met een visuele beperking. 27 Tarallo, A. D. S., Hiraga, A. K., Martinez, G. A. G., Paiva, M. S. V. D., Jorge, L. A. D. C., & Senger, H. (2013). Parallel Processing Applied to Image Mosaic Generation. In IX Workshop de Vis�o Computacional (WVC 2013). Universidade Federal Fluminense (UFF). 28 Naftalianto, Y. (2012). RancangBangun Sensor Jarak Dengan Korespondensi Citra Dengan Ekstraksi Fitur SURF Dan Konsep Stereo Vision. Jurnal Sarjana Teknik Elektro, 1(1). 29 Meisel, A. Andreas Liedtke Realisierung eines robusten Verfahrens zur Identifikation von Positionsmarken unter Verwendung von Bildverarbeitung in Videobildern. 30 Kim, J. Y., Jeong, S. W., Jeong, M. B., Han, H. J., Kim, J. S., Park, H. M., & Chung, B. H. (2002). Application of total ear canal ablation and Ferreira, A. L. S., Santos, S. R. D., & de Miranda, L. C. (2012, May). TrueSight A Pedestrian Navigation System Based in Automatic Landmark Detection and Extraction on Android Smartphone. In Virtual and Augmente 31 Augereau, O., Journet, N., & Domenger, J. P. (2013). Reconnaissance et extraction de documents. Document num�rique, 16(2), 91-118. 32 Laura, T. L. (2013). Sistema de supervis�o a�rea baseado em navega��o visual para detec��o de anomalias em instala��es de petr�leo e g�s. 33 Wang, P. H. (2011). Implementation of fast SIFT feature extraction and matching using GPU. 34 Mota, I. F. V. (2014). Olh�-passarinho: uma extens�o do TweeProfiles para fotografias (Doctoral dissertation, Master�s thesis, Faculdade de Engenharia da Universidade do Porto). 35 Salamon, N. Z. (2015). Re-identifica��o de pessoas em imagens atrav�s de caracter�sticas descritivas de cores e grupos. 36 Couto, L., & Os�rio, F. Auto-Localiza��o Aut�noma de Rob�s M�veis por Vis�o Computacional Baseada em Pontos de Refer�ncia. 37 Shukla, A. P., & Saini, M. (2015). �Moving Object Tracking of Vehicle Detection�: A Concise Review. International Journal of Signal Processing, Image Processing and Pattern Recognition, 8(3), 169-176. 38 Aguilar, W. G., & Angulo, C. (2015). Real-Time Model-Based Video Stabilization for Microaerial Vehicles. Neural Processing Letters, 1-19. 39 Solehah, S., Yaakob, S. N., Kadim, Z., & Woon, H. H. (2012, December). Moving object extraction in PTZ camera using the integration of background subtraction and local histogram processing. In Computer Applications and Industrial Electronics (ISCAIE), 2012 IEEE Symposium on (pp. 167-172). IEEE. 40 Xie, Z., Chen, J., Yao, T., & Sun, Y. (2015). Geometric structure-constraint tracking with confident parts. Signal Processing: Image Communication, 36, 43-52. 41 Jayachandran, G., Ekin, A., & De Haan, I. G. (2012). Landmark detection in MR brain images using SURF. 42 Lin, S. C. F., Wong, C. Y., Jiang, G., Rahman, M. A., & Kwok, N. M. (2014). Radial Fourier Analysis (RFA) Descriptor with Fourier-based Keypoint Orientation. International Journal of Image Processing (IJIP), 8(6), 397. 43 Xiong, X., & Choi, B. J. (2013, January). Estimation of Relative Self-Localization Based On Natural Landmark and an Improved SURF. In Proceedings of World Academy of Science, Engineering and Technology (No. 73, p. 900). World Academy of Science, Engineering and Technology (WASET). 44 Xiong, P., Liu, X., Gao, C., Zhou, Z., Gao, C., & Liu, Q. (2013, March). A Real-time Stitching Algorithm for UAV Aerial Images. In Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering. Atlantis Press. 45 Averkin, A. N. (2010). Training image-correlation systems by optimizing their attribute representations. Journal of Optical Technology, 77(11), 712-720. 46 Koel, F., Maurer, R. K., & Prieler, Z. R. A Survey on Action Recognition Using Kinematic Feature Extraction Techniques. 47 Xiong, X., & Choi, B. J. (2013). Estimation of Relative Self-Localization for Indoor Mobile Robot and Its Error Analysis. International Journal of Smart Home, 7(4), 69-76. 48 Lin, C. H., & Chen, A. Y. Trip Characteristics Study through Social Media Data. 49 Wang, Z., & Qureshi, F. Z. (2013, May). Topic models for image localization. In Computer and Robot Vision (CRV), 2013 International Conference on (pp. 136-143). IEEE. 50 Li, X., Aouf, N., & Nemra, A. (2012, September). Estimation analysis in VSLAM for UAV application. In Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on (pp. 365370). IEEE. 51 Jain, S., & Kanwal, N. (2014, November). Overview on image registration. In Medical Imaging, mHealth and Emerging Communication Systems (MedCom), 2014 International Conference on (pp. 376-381). IEEE. 52 Potgieter, M., & Van Niekerk, J. (2013). MULTI-AGENT AUGMENTED COMPUTER VISION TECHNOLOGIES TO SUPPORT HUMAN MONITORING OF SECURE COMPUTING FACILITIES. SAIEE Africa Research Journal, 80. 53 Jurgensen, S. M. (2014). The rotated speeded-up robust features algorithm (R-SURF). NAVAL POSTGRADUATE SCHOOL MONTEREY CA. 54 Singh, K., & Chander, S. (2014). CONTENT BASED IMAGE RETRIEVAL WITH SURF, SVM AND COLOR HISTOGRAM. 55 Issac, A., & Velayutham, C. S. (2012). SaddleSURF: A Saddle Based Interest Point Detector. In Mathematical Modelling and Scientific Computation (pp. 413-420). Springer Berlin Heidelberg. 56 Sharma, B., & Sharma, A. (2015). A REVIEW: CONTENT BASED IMAGE RETRIEVAL WITH SURF AND COLOUR HISTOGRAM USING CROSS VALIDATION AND GRAPH MATCHING ON MEDICAL IMAGES. International Journal, 1(4). 57 Walsh, R., & Hornsby, A. (2011, January). Toward