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研究生:賴彥菱
研究生(外文):Yen-Ling Lai
論文名稱:使用匹配濾波器之貨櫃車車尾影像偵測研究
論文名稱(外文):Container Rear End Image Detection using Matched Filters
指導教授:李建誠李建誠引用關係
指導教授(外文):Chien-Cheng Lee
口試委員:黃春融鄭旭詠
口試委員(外文):Chun-Rong HuangHsu-Yung Cheng
口試日期:2014-08-14
學位類別:碩士
校院名稱:元智大學
系所名稱:通訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
畢業學年度:103
語文別:中文
論文頁數:44
中文關鍵詞:貨櫃車尾偵測匹配濾波器支援向量機
外文關鍵詞:Container Rear End Image DetectionMatched FilterSupport Vector Machine
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本研究提出一套偵測貨櫃車車尾區域影像之方法,擷取出的貨櫃車車尾影像,可用來當作貨櫃的外觀特徵 (appearance feature),以強化貨櫃的識別監視系統。本方法首先以匹配濾波器偵測不同角度的線段,之後找出這些線段所組合而成的所有四邊形,再針對這些四邊形擷取特徵進行過濾,找出符合貨櫃車車尾樣式的四邊形,在我們實驗的過程中,辨識率高達99.8%,證明本方法在貨櫃車車尾區域的偵測問題上,確實可行。
This paper proposed a method for detecting the container rear end images. The container rear end images can be regarded as appearance features of a container to enhance the container recognition and surveillance system. To detect the container rear end images, the method uses a matched filter to detect different directions of lines in the container rear end images. Then, we find quadrilaterals which are composed of all combinations of lines. Afterwards, quadrilateral features are extracted and fed into a support vector machine (SVM) classifier to train a model for container rear end image recognition. Then, the model is used to detect the quadrilaterals from container rear end images in the testing phase. Finally, a correct procedure is used to correct the classification error. In the experimental results, the accuracy rate is 99.8%. The result shows that the proposed method can be applied to the container rear end images recognition.
書名頁 ..................................ii
審定書 ..................................iii
中文摘要 ..................................iv
英文摘要 ..................................v
誌 謝 ...................................vi
目 錄 ...................................vii
第一章、 序論 ............................1
1.1 研究背景 .............................1
1.2 本研究之貢獻 .............................2
1.3 論文架構 .............................2
第二章、 文獻探討 ......................3
2.1 物件偵測 .............................3
2.2 車輛偵測 .............................5
2.3 線段偵測 .............................6
第三章、 研究方法 .....................8
3.1貨櫃車影像結構介紹 ....................8
3.2貨櫃偵測流程 ...........................9
3.3貨櫃影像前處理 ...........................10
3.4匹配濾波器 ...........................13
3.4.1匹配濾波器核心設置 ..................14
3.4.2線段合併 ...........................18
3.4.3線段交點偵測 ...........................22
3.5 特徵擷取 ............................23
3.6 支援向量機 ..........................29
3.7 分類器錯誤校正 ......................32
第四章、 實驗結果與討論 ................36
4.1 資料來源 ............................36
4.2 實驗流程 ............................37
4.3 貨櫃車尾區域偵測評估方式 .............38
4.4 貨櫃車尾區域偵測之測試結果 ...........39
第五章、 結論與未來展望 ...............41
參考文獻 ................................42

[1] Container Handbook. Available: http://www.tis-gdv.de/tis_e/publikationen/chb.htm
[2] K. B. Kim, Y. W. Woo, and H. K. Yang, "An intelligent system for container image recognition using ART2-based self-organizing supervised learning algorithm," in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) vol. 4247 LNCS, ed, 2006, pp. 897-904.
[3] K. M. Koo and E. Y. Cha, "A novel container ISO-code recognition method using texture clustering with a spatial structure window," International Journal of Software Engineering and its Applications, vol. 7, pp. 51-62, 2013.
[4] S. Kumano, K. Miyamoto, M. Tamagawa, H. Ikeda, and K. Kan, "Development of a container identification mark recognition system," Electronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi), vol. 87, pp. 38-50, 2004.
[5] Container ID recognition library. Available: http://www.neurallabs.net/en/ocr-systems/container-id-recognition/
[6] TeleRadio Container Number Recognition System (CNRS). Available: http://www.uvss.com
[7] SeeGateInformation-Container Code Recognition. Available: http://www.htsol.com/
[8] M. J. Swain and D. H. Ballard, "Color indexing," International Journal of Computer Vision, vol. 7, pp. 11-32, 1991.
[9] B. Schiele and J. L. Crowley, "Recognition without correspondence using multidimensional receptive field histograms," International Journal of Computer Vision, vol. 36, pp. 31-50, 2000.
[10] T. Leung and J. Malik, "Representing and recognizing the visual appearance of materials using three-dimensional textons," International Journal of Computer Vision, vol. 43, pp. 29-44, 2001.
[11] H. Schneiderman and T. Kanade, "Statistical method for 3D object detection applied to faces and cars," in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2000, pp. 746-751.
[12] N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, 2005, pp. 886-893.
[13] I. Laptev, "Improving object detection with boosted histograms," Image and Vision Computing, vol. 27, pp. 535-544, 2009.
[14] K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis, "Real-time foreground-background segmentation using codebook model," Real-Time Imaging, vol. 11, pp. 172-185, 2005.
[15] S. Gupte, O. Masoud, R. F. K. Martin, and N. P. Papanikolopoulos, "Detection and Classification of Vehicles," IEEE Transactions on Intelligent Transportation Systems, vol. 3, pp. 37-47, 2002.
[16] N. A. Mandellos, I. Keramitsoglou, and C. T. Kiranoudis, "A background subtraction algorithm for detecting and tracking vehicles," Expert Systems with Applications, vol. 38, pp. 1619-1631, 2011.
[17] M. Vargas, J. M. Milla, S. L. Toral, and F. Barrero, "An enhanced background estimation algorithm for vehicle detection in urban traffic scenes," IEEE Transactions on Vehicular Technology, vol. 59, pp. 3694-3709, 2010.
[18] Z. Sun, G. Bebis, and R. Miller, "On-road vehicle detection: A review," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, pp. 694-711, 2006.
[19] Z. Sun, G. Bebis, and R. Miller, "Monocular precrash vehicle detection: Features and classifiers," IEEE Transactions on Image Processing, vol. 15, pp. 2019-2034, 2006.
[20] L. W. Tsai, J. W. Hsieh, and K. C. Fan, "Vehicle detection using normalized color and edge map," IEEE Transactions on Image Processing, vol. 16, pp. 850-864, 2007.
[21] H. P. V. C. (1962). Method and means for recognizing complex patterns. Available: http://www.google.com/patents/US3069654
[22] R. O. Duda and P. E. Hart, "Use of the Hough transformation to detect lines and curves in pictures," Communications of the ACM, vol. 15, pp. 11-15, 1972.
[23] O. Chutatape and L. Guo, "A modified Hough transform for line detection and its performance," Pattern Recognition, vol. 32, pp. 181-192, 1999.
[24] S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum, "Detection of blood vessels in retinal images using two-dimensional matched filters," IEEE Transactions on Medical Imaging, vol. 8, pp. 263-269, 1989.
[25] A. Hoover, "Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response," IEEE Transactions on Medical Imaging, vol. 19, pp. 203-210, 2000.
[26] M. Al-Rawi, M. Qutaishat, and M. Arrar, "An improved matched filter for blood vessel detection of digital retinal images," Computers in Biology and Medicine, vol. 37, pp. 262-267, 2007.
[27] N. Patton, T. M. Aslam, T. MacGillivray, I. J. Deary, B. Dhillon, R. H. Eikelboom, et al., "Retinal image analysis: Concepts, applications and potential," Progress in Retinal and Eye Research, vol. 25, pp. 99-127, 2006.
[28] D. Song, B. Zhao, and L. Tang, "A real-time middle wavelength infrared multi-target detection and tracking algorithm based on LoG," in Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011, 2011, pp. 127-131.
[29] M. Heath, S. Sarkar, T. Sanocki, and K. Bowyer, "Comparison of Edge Detectors: A Methodology and Initial Study," Computer Vision and Image Understanding, vol. 69, pp. 38-54, 1998.
[30] Sobel Edge Detector. Available: http://homepages.inf.ed.ac.uk/rbf/HIPR2/sobel.htm
[31] Laplacian/Laplacian of Gaussian. Available: http://homepages.inf.ed.ac.uk/rbf/HIPR2/log.htm
[32] M. Al-Rawi and H. Karajeh, "Genetic algorithm matched filter optimization for automated detection of blood vessels from digital retinal images," Computer Methods and Programs in Biomedicine, vol. 87, pp. 248-253, 2007.
[33] B. Zhang, L. Zhang, L. Zhang, and F. Karray, "Retinal vessel extraction by matched filter with first-order derivative of Gaussian," Computers in Biology and Medicine, vol. 40, pp. 438-445, 2010.
[34] P. F. Felzenszwalb and D. P. Huttenlocher, "Distance Transforms of Sampled Functions," Theory of Computing, vol. 8, pp. 415-428, 2012.
[35] G. Borgefors, "Distance transformations in digital images," Computer Vision, Graphics, &; Image Processing, vol. 34, pp. 344-371, 1986.
[36] J. M. Bland and D. G. Altman, "Statistical methods for assessing agreement between two methods of clinical measurement," Lancet, vol. 1, pp. 307-310, 1986.
[37] C. Cortes and V. Vapnik, "Support-vector networks," Machine Learning, vol. 20, pp. 273-297, 1995.
[38] C.-C. Chang and C.-J. Lin. LIBSVM -- A Library for Support Vector Machines. Available: http://www.csie.ntu.edu.tw/~cjlin/libsvm/
[39] T. Fawcett, "An introduction to ROC analysis," Pattern Recognition Letters, vol. 27, pp. 861-874, 2006.
[40] C. A. Lupaşcu, D. Tegolo, and E. Trucco, "FABC: Retinal vessel segmentation using AdaBoost," IEEE Transactions on Information Technology in Biomedicine, vol. 14, pp. 1267-1274, 2010.

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