Automated color model-based concrete detection in construction-site images by using machine learning algorithms

Journal of Computing in Civil Engineering

Volumn 26, Issue 3, 2012, Pages 421-433

  Kim, Changwan ^a   Son, Hyojoo ^a   Kim, Changmin ^a  

^a Chung Ang University   (South Korea)

Author keywords

Artificial neural networks; Color space transformation; Concrete structural component; Gaussian mixture models; Machine learning algorithm; Support vector machines

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; COLOR IMAGES; COLOR SPACE; COLOR-SPACE TRANSFORMATION; CONCRETE SURFACE; DATA SETS; DETECTION METHODS; GAUSSIAN MIXTURE MODEL; HSI COLOR SPACE; NORMALIZED RGB; OPTIMAL COMBINATION; PROGRESS MEASUREMENT; RGB COLOR SPACE; STRUCTURAL COMPONENT; SUPPORT VECTOR; SUPPORT VECTOR MACHINE ALGORITHM;

COLOR; COLOR IMAGE PROCESSING; COMMUNICATION CHANNELS (INFORMATION THEORY); LEARNING SYSTEMS; NEURAL NETWORKS; OBJECT RECOGNITION; SUPPORT VECTOR MACHINES; THREE DIMENSIONAL;

LEARNING ALGORITHMS;

EID: 84861110538     PISSN: 08873801     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)CP.1943-5487.0000141     Document Type: Article

References (75)

1. Abdesselam, A., and Abdullah, R. C. (2000). Pepper berries grading using artificial neural networks. Proc., IEEE Region 10 Conf., IEEE, New York, 153-159.
2. Baek, N., Park, S.-M., Kim, K.-J., and Park, S.-B. (2007). Vehicle color classification based on the support vector machine method. Proc., 3rd Int. Conf. on Intelligent Computing, Springer, Berlin Heidelberg, Germany, 1133-1139.
3. Barth, A., and Herpers, R. (2005). Robust head detection and tracking in cluttered workshop environments using GMM. Proc., 27th Deutsche Arbeitsgemeinschaft fr Mustererkennung Symp., Springer, Berlin Heidelberg, Germany, 442-450. (Pubitemid 41520685)
4. Bascle, B., Bernier, O., and Lemaire, V. (2006). Illumination-invariant color image correction. Proc., Int. Workshop on Intelligent Computing in Pattern Analysis/Synthesis, Springer, Berlin Heidelberg, Germany, 359-368. (Pubitemid 44577695)
5. Basu, J. K., Bhattacharyya, D., and Kim, T.-H. (2010). Use of artificial neural network in pattern recognition. Int. J. Software Eng. Appl. 1738-9984, 4 (2), 23-34.
6. Caetano, T. S., Olabarriaga, S. D., and Barone, D. A. C. (2003). Do mixture models in chromaticity space improve skin detection? Pattern Recognit., 36 (12), 3019-3021. PTNRA8 0031-3203 10.1016/S0031-3203(03)00116-X (Pubitemid 37293410)
7. Cavalin, P., Oliveira, L. S., Koerich, A. L., and Britto, A. S. (2006). Wood defect detection using grayscale images and an optimized feature set. Proc., 32nd Annual Conf. on IEEE Industrial Electronics, IEEE, New York, 3408-3412.
8. Chang, K. T., and Liu, J. K. (2004). Landslide features interpreted by neural network method using a high-resolution satellite image and digital topographic data. Proc., 20th Int. Society for Photogrammetry and Remote Sensing Congress, International Society for Photogrammetry and Remote Sensing (ISPRS), Enschede, Netherlands, 574-579.
9. Chen, Q., Zhao, J., Fang, C. H., and Wang, D. (2007). Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM). Spectrochim. Acta, Part A, 66 (3), 568-574. SAMCAS 1386-1425 10.1016/j.saa.2006.03.038 (Pubitemid 46199298)
10. Chen, R.-C., Luo, S.-T., Liang, X., and Lee, V. C. S. (2005). Personalized approach based on SVM and ANN for detecting credit card fraud. Proc., Int. Conf. on Neural Networks and Brain, IEEE, New York, 810-815. (Pubitemid 46289075)
11. Chen, X., Xun, Y., Li, W., and Zhang, J. (2010). Combining discriminant analysis and neural networks for corn variety identification. Comput. Electron. Agric., 71 (1), S48-S53. CEAGE6 0168-1699 10.1016/j.compag.2009.09.003
12. Chen, Z., Pears, N., Freeman, M., and Austin, J. (2009). Road vehicle classification using support vector machines. Proc., IEEE Int. Conf. on Intelligent Computing and Intelligent Systems, IEEE, New York, 214-218.
13. Cheng, H. D., Jiang, X. H., Sun, Y., and Wang, J. (2001). Color image segmentation: Advances and prospects. Pattern Recognit., 34 (12), 2259-2281. PTNRA8 0031-3203 10.1016/S0031-3203(00)00149-7 (Pubitemid 32961807)
14. Coussement, K., and Van den Poel, D. (2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. Expert Syst. Appl., 34 (1), 313-327. ESAPEH 0957-4174 10.1016/j.eswa.2006.09.038 (Pubitemid 46756260)
15. DeLurgio, S. A. (1998). Forecasting principles and applications, Irwin/McGraw-Hill, Boston.
16. Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximum-likelihood from incomplete data via the EM algorithm. J. R. Statist. Soc. B, 39 (1), 1-38. 1369-7412
17. Ding, Y., Song, X., and Zen, Y. (2008). Forecasting financial condition of Chinese listed companies based on support vector machine. Expert Syst. Appl., 34 (4), 3081-3089. ESAPEH 0957-4174 10.1016/j.eswa.2007.06.037 (Pubitemid 351173811)
18. Du, C.-J., and Sun, D.-W. (2005). Comparison of three methods for classification of pizza topping using different colour space transformations. J. Food Eng., 68 (3), 277-287. JFOEDH 0260-8774 10.1016/j.jfoodeng.2004.05.044
19. Duda, R. O., and Hart, P. E. (1973). Pattern classification and scene analysis, Wiley Interscience, New York.
20. El-Sanhoty, R., Shahwan, T., and Ramadan, M. F. (2006). Application of artificial neural networks to develop a classification model between genetically modified maize (Bt-176) and conventional maize by applying lipid analysis data. J. Food Compos. Anal., 19 (6-7), 628-636. JFCAEE 0889-1575 10.1016/j.jfca.2006. 03.013 (Pubitemid 43827553)
21. Fei-Fei, L., Fergus, R., and Perona, P. (2003). A Bayesian approach to unsupervised one-shot learning of object categories. Proc., 9th IEEE Int. Conf. on Computer Vision, IEEE Computer Society, Washington, DC, 1134-1141.
22. Greenspan, H., Goldberger, J., and Eshet, I. (2001). Mixture model for face-color modeling and segmentation. Pattern Recognit. Lett., 22 (14), 1525-1536. PRLEDG 0167-8655 10.1016/S0167-8655(01)00086-1 (Pubitemid 32944187)
23. Hjelms, E., and Low, B. K. (2001). Face detection: A survey. Comput. Vision Image Understanding, 83 (3), 236-274. CVIUF4 1077-3142 10.1006/cviu.2001.0921 (Pubitemid 33024376)
24. Hornik, K., Stinchcombe, M., and White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Netw., 2 (5), 359-366. NNETEB 0893-6080 10.1016/0893-6080(89)90020-8 (Pubitemid 20609008)
25. Huang, C.-L., Chen, M.-C., and Wang, C.-J. (2007). Credit scoring with a data mining approach based on support vector machines. Expert Syst. Appl., 33 (4), 847-856. ESAPEH 0957-4174 10.1016/j.eswa.2006.07.007 (Pubitemid 46522466)
26. Jain, A. K. (1989). Fundamentals of digital image processing, Prentice-Hall, Upper Saddle River, NJ.
27. Jones, M. J., and Rehg, J. M. (2002). Statistical color models with application to skin detection. Int. J. Comput. Vision, 46 (1), 81-96. IJCVEQ 0920-5691 10.1023/A:1013200319198 (Pubitemid 34138494)
28. Ju, J., Kolaczyk, E. D., and Gopal, S. (2003). Gaussian mixture discriminant analysis and sub-pixel land cover characterization in remote sensing. Remote Sens. Environ., 84 (4), 550-560. RSEEA7 0034-4257 10.1016/S0034-4257(02)00172-4 (Pubitemid 36360516)
29. Juang, C.-F., Chiu, S.-H., and Shiu, S.-J. (2007). Fuzzy system learned through fuzzy clustering and support vector machine for human skin color segmentation. IEEE Trans. Syst. Man Cybern. Part A: Syst. Humans, 37 (6), 1077-1087. ITSHFX 1083-4427 10.1109/TSMCA.2007.904579 (Pubitemid 350130845)
30. Kaastra, I., and Boyd, M. (1996). Designing a neural network for forecasting financial and economic time series. Neurocomputing: Variable Star Bull., 10 (3), 215-236. NRCGEO 0925-2312 10.1016/0925-2312(95)00039-9 (Pubitemid 26133281)
31. Kakumanu, P., Makrogiannis, S., and Bourbakis, N. (2007). A survey of skin-color modeling and detection methods. Pattern Recognit., 40 (3), 1106-1122. PTNRA8 0031-3203 10.1016/j.patcog.2006.06.010 (Pubitemid 44667749)
32. Karlekar, J., and Desai, U. B. (1999). Finding faces in color images using wavelet transform. Proc., Int. Conf. on Image Analysis and Processing, IEEE, New York, 1085-1088.
33. Khun, P. C., Zhuo, Z., Yang, L. Z., Liyuan, L., and Jiang, L. (2009). Feature selection and classification for wireless capsule endoscopic frames. Proc., Int. Conf. on Biomedical and Pharmaceutical Engineering, IEEE, New York, 1-6.
34. Kl, K., Boyaci,. H., Kksel, H., and Ksmenolu,. (2007). A classification system for beans using computer vision system and artificial neural networks. J. Food Eng., 78 (3), 897-904. JFOEDH 0260-8774 10.1016/j.jfoodeng.2005.11.030
35. Krstinić, D., Stipaniev, D., and Jakovević, T. (2009). Histogram-based smoke segmentation in forest fire detection system. Inf. Technol. Control 1392-124X, 38 (3), 237-244.
36. Kurata, T., Okuma, T., Kourogi, M., and Sakaue, K. (2001). The hand mouse: GMM hand-color classification and mean shift tracking. Proc., IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, IEEE, New York, 119-124.
37. Lee, Y., Lee, K. Y., and Lee, J. (2006). The estimating optimal number of Gaussian mixtures based on incremental k-means for speaker identification. Int. J. Inf. Technol. 0218-7957, 12 (7), 13-21.
38. Lee, Y.-C. (2007). Application of support vector machines to corporate credit rating prediction. Expert Syst. Appl., 33 (1), 67-74. ESAPEH 0957-4174 10.1016/j.eswa.2006.04.018 (Pubitemid 44959918)
39. Maldonado-Bascon, S., Lafuente-Arroyo, S., Gil-Jimenez, P., Gomez-Moreno, H., and Lopez-Ferreras, F. (2007). Road-sign detection and recognition based on support vector machines. IEEE Trans. Intell. Transp. Syst., 8 (2), 264-278. 1524-9050 10.1109/TITS.2007.895311 (Pubitemid 46873208)
40. Marchesotti, L., Messina, A., Marcenaro, L., and Regazzoni, C. (2003). A cooperative multisensor system for face detection in video surveillance applications. Acta Autom. Sin., 29 (3), 423-433. THHPAY 0254-4156
41. Miller, S. H. (2008). An inclination for innovation. PTI Journal, August, 51-56.
42. Mora, M., and Sbarbaro, D. (2005). A robust footprint detection using color images and neural networks. Proc., 10th Iberoamerican Congress on Pattern Recognition, Springer, Berlin Heidelberg, Germany, 311-318. (Pubitemid 43943637)
43. Neto, J. A., Arditi, D., and Evens, M. W. (2002). Using colors to detect structural components in digital pictures. Comput. Aided Civ. Infrastruct. Eng., 17 (1), 61-67. CCIEFR 1093-9687 10.1111/1467-8667.00253 (Pubitemid 34152636)
44. Nevatia, R. (1977). A color edge detector and its use in scene segmentation. IEEE Trans. Syst. Man Cybern., 7 (11), 820-826. ISYMAW 0018-9472 10.1109/TSMC.1977.4309631
45. Nguwi, Y.-Y., and Kouzani, A. Z. (2008). Detection and classification of road signs in natural environments. Neural Comput. Appl., 17 (3), 265-289. NCAPF5 0941-0643 10.1007/s00521-007-0120-z
46. Pandey, P. C., and Barai, S. V. (1995). Multilayer perceptron in damage detection of bridge structures. Comput. Struct. CMSTCJ 0045-7949, 54 (4), 597-608. 10.1016/0045-7949(94)00377-F
47. Papageorgiou, C., and Poggio, T. (2000). A trainable system for object detection. Int. J. Comput. Vision, 38 (1), 15-33. IJCVEQ 0920-5691 10.1023/A:1008162616689
48. Prez-Magario, S., Ortega-Heras, M., Gonzlez-San, Jos M. L., and Boger, Z. (2004). Comparative study of artificial neural network and multivariate methods to classify Spanish DO rose wines. Talanta, 62 (5), 983-990. TLNTA2 0039-9140 10.1016/j.talanta.2003.10.019
49. Phung, S. L., Chai, D., and Bouzerdoum, A. (2001). A universal and robust human skin color model using neural networks. Proc., Int. Joint Conf. on Neural Networks, IEEE, Washington, DC, 2844-2849. (Pubitemid 32794762)
50. Quan, H.-T., Meguro, M., and Kaneko, M. (2002). Skin-color extraction in images with complex background and varying illumination. Proc., 6th IEEE Workshop on Applications of Computer Vision, IEEE, New York, 280-285.
51. Redner, R. A., and Walker, H. F. (1984). Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev., 26 (2), 195-239. SIREAD 0036-1445 10.1137/1026034
52. Reynolds, D. A., and Rose, R. C. (1995). Robust text-independent speaker verification using Gaussian mixture speaker models. IEEE Trans. Speech Audio Process., 3 (1), 72-83. IESPEJ 1063-6676 10.1109/89.365379
53. Richards, T. J., Patterson, P. M., and van Ispelen, P. (1998). Modeling fresh tomato marketing margins: Econometrics and neural networks. Agric. Resour. Econ. Rev. 1068-2805, 27 (2), 186-199. (Pubitemid 128164772)
54. Rubinstein, Y. D., and Hastie, T. (1997). Discriminative vs informative learning. Proc., 3rd Int. Conf. on Knowledge Discovery and Data Mining, American Association for Artificial Intelligence, Palo Alto, California, 49-53.
55. Sahbi, H., and Boujemaa, N. (2002). Coarse to fine face detection based on skin color adaption. Proc., ECCV's 2002 Workshop on Biometric Authentication, Springer, Berlin Heidelberg, Germany, 112-120.
56. Schmugge, S. J., Jayaram, S., Shin, M. C., and Tsap, L. V. (2007). Objective evaluation of approaches of skin detection using ROC analysis. Comput. Vision Image Understanding, 108 (1-2), 41-51. CVIUF4 1077-3142 10.1016/j.cviu.2006.10.009 (Pubitemid 47333388)
57. Seow, M.-J., Valaparla, D., and Asari, V. K. (2003). Neural network based skin color model for face detection. Proc., 32nd Applied Imagery Pattern Recognition Workshop, IEEE Computer Society, Washington, DC, 141-145.
58. Sivic, J., Zitnick, C. L., and Szeliski, R. (2006). Finding people in repeated shots of the same scene. Proc., 16th British Machine Vision Conf., British Machine Vision Association, Malvern, United Kingdom, 909-918.
59. Steenhoek, L. W., Misra, M. K., Batchelor, W. D., and Davidson, J. L. (2001). Probabilistic neural networks for segmentation of features in corn kernel images. Appl. Eng. Agric., 17 (2), 225-234. 0883-8542 (Pubitemid 33046506)
60. Sugumaran, V., Sabareesh, G. R., and Ramachandran, K. I. (2008). Fault diagnostics of roller bearing using kernel based neighborhood score multi-class support vector machine. Expert Syst. Appl., 34 (4), 3090-3098. ESAPEH 0957-4174 10.1016/j.eswa.2007.06.029 (Pubitemid 351173812)
61. Swain, M. J., and Ballard, D. H. (1991). Color indexing. Int. J. Comput. Vision, 7 (1), 11-32 IJCVEQ 0920-5691. 10.1007/BF00130487
62. Terrillon, J.-C., Fukamachi, H., Akamatsu, S., and Shirazi, M. N. (2000). Comparative performance of different skin chrominance models and chrominance spaces for the automatic detection of human faces in color images. Proc., 4th IEEE Int. Conf. on Automatic Face and Gesture Recognition, IEEE, New York, 54-61.
63. Tyree, E. W., and Long, J. A. (1995). Forecasting currency exchange rates: Neural networks and the random walk model. Proc., 3rd Int. Conf. on Artificial Intelligence Applications, Software Engineering Press, New York.
64. Vapnik, V. N. (1999). An overview of statistical learning theory. IEEE Trans. Neural Netw., 10 (5), 988-999. ITNNEP 1045-9227 10.1109/72.788640
65. Vezhnevets, V., Sazonov, V., and Andreeva, A. (2003). A survey on pixel-based skin color detection techniques. Proc., 13th Int. Conf. on the Computer Graphics and Vision, Moscow State Univ., Moscow, 85-92.
66. Wang, Y., and Yuan, B. (2001). A novel approach for human face detection from color images under complex background. Pattern Recognit., 34 (10), 1983-1992. PTNRA8 0031-3203 10.1016/S0031-3203(00)00119-9 (Pubitemid 32760628)
67. Wesolkowski, S. (1999). Color image edge detection and segmentation: A comparison of the vector angle and the Euclidean distance color similarity measures. M.S. thesis, Dept. of Systems Design Engineering, Univ. of Waterloo, ON, Canada.
68. Widodo, A., Yang, B.-S., and Han, T. (2007). Combination of independent component analysis and support vector machines for intelligent faults diagnosis of induction motors. Expert Syst. Appl., 32 (2), 299-312. ESAPEH 0957-4174 10.1016/j.eswa.2005.11.031 (Pubitemid 44647799)
69. Wu, J.-D., and Ye, S.-H. (2009). Driver identification based on voice signal using continuous wavelet transform and artificial neural network techniques. Expert Syst. Appl., 36 (2), 1061-1069. ESAPEH 0957-4174 10.1016/j.eswa.2007.11.003
70. Wu, T.-K., Huang, S.-C., and Meng, Y.-R. (2008). Evaluation of ANN and SVM classifiers as predictors to the diagnosis of students with learning disabilities. Expert Syst. Appl., 34 (3), 1846-1856. ESAPEH 0957-4174 10.1016/j.eswa.2007.02.026 (Pubitemid 350298207)
71. Yang, M.-H., and Ahuja, N. (1999). Gaussian mixture model for human skin color and its applications in image and video databases. Proc., SPIE: Storage and Retrieval for Image and Video Database, Society of Photo-optical Instrumentation Engineers (SPIE), Bellingham, WA, 458-466.
72. Yoo, P. D., Kim, M. H., and Jan, T. (2005). Machine learning techniques and use of event information for stock market prediction: A survey and evaluation. Proc., Int. Conf. on Computational Intelligence for Modelling, Control and Automation and Int. Conf. on Intelligent Agents, Web Technologies and Internet Commerce, IEEE, New York, 835-841.
73. Zhiwei, L., and Minfen, S. (2007). Classification of mental task EEG signals using wavelet packet entropy and SVM. Proc., 8th Int. Conf. on Electronic Measurement and Instruments, IEEE, New York,.
74. Zhu, S., and Liu, L. (2006). Traffic sign recognition based on color standardization. Proc., IEEE Int. Conf. on Information Acquisition, IEEE, New York, 951-955.
75. Zhu, Z., and Brilakis, I. (2010). Parameter optimization for automated concrete detection in image data. Autom. Constr., 19 (7), 944-953. AUCOES 0926-5805 10.1016/j.autcon.2010.06.008