Development of image processing and vision systems with industrial applications

Development of Image Processing and Vision Systems with Industrial Applications Zhang Yi A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2009 Acknowledgments I would like to express my sincerest appreciation to all who had helped me during my study in National University of Singapore. First of all, I would like to thank my supervisors Associate Professor Tan Kok Kiong for his inspirational discussions, support and encouragement. His vision and passion for research enlighten my research work and spurred my creativity. I would like to give my gratitude to all my friends in Mechatronics and Automation Lab. I would especially like to thank Dr. Huang Sunan, Dr. Tang Kok Zuea, Mr. Tan Chee Siong, Dr. Zhao Shao, Dr. Teo Chek Sing, Dr. Andi Sudjana Putra, Mr. Chen Silu and Mr. Yuan Jian for their helpful discussions and advice. I would also wish to thank Ms Lay Geok from Medical Department, NUS for her assistance for my experiment. Finally, I would like to thank my family for their endless love and support. II CONTENTS Acknowledgments .II List of Figures . IV List of Tables VI List of Abbreviations .VII Summary .VIII CHAPTER Introduction . 1.1 Impact of Computer Imaging Technologies . 1.2 Contributions . 1.2.1 Text Extraction and Translation . 1.2.2 Vision-based Automatic Cell Manipulation System 1.2.3 Vision-assisted thermal tracking system for CNC machine 1.3 Organization of Thesis . CHAPTER Text Extraction and Translation from Images Captured via Mobile and Digital Devices . 2.1 Introduction . 2.2 Text Extraction 14 2.2.1 Color to Gray Scale Transformation 14 2.2.2 Region Segmentation . 15 III 2.3 Character Recognition . 20 2.4 Experimental Results 23 2.5 Conclusions 26 CHAPTER Vision-Servo System for Automated Cell Injection . 27 3.1 Introduction 27 3.2 System Setup 32 3.3 Cell Detection . 33 3.4 Pipette Detection 39 3.5 Tip Focalization . 41 3.6 Penetration 43 3.7 Validation . 45 3.8 Conclusions 47 CHAPTER Vision-based Tracking and Monitoring System for CNC Machine Surveillance . 48 4.1 Introduction . 48 4.2 Background and problem statement 50 4.3 Distributed Wireless Sensor Network for CNC Machine Surveillance 51 4.4 Decoupled Tracking and Thermal Monitoring of Non-Stationary Targets58 4.4.1 Overall System Configuration . 59 4.4.2 Vision and Image Processing System 63 4.4.3 Non-Contact Temperature Measurement System 68 4.4.4 Tracking Control of Linear Motor . 69 IV 4.4.5 Practical Issues . 74 4.4.6 Experimental Results . 77 4.4.7 Conclusions 85 CHAPTER Conclusions . 87 5.1 Summary of Contributions 87 5.2 Suggestions for future work 89 Author’s Publications 92 Bibliography 94 V List of Figures Fig. 2.1 Sample images taken by mobile phones 11 Fig. 2.2 Flowchart of text extraction algorithm 13 Fig. 2.3 Image after Gray Scale Transformation . 14 Fig. 2.4 Edge Detection Kernels . 16 Fig. 2.5 Background separation 17 Fig. 2.6 Unwanted parts elimination . 18 Fig. 2.7 Abnormal Object Removal 20 Fig. 2.8 Pictorial Definition 22 Fig. 3.1 Bio-manipulation System 28 Fig. 3.2 Vision-assisted Servo System 29 Fig. 3.3 Flowchart of Process 30 Fig. 3.4 Two steps in system setup . 33 Fig. 3.5 Hough circle detection . 35 Fig. 3.6 Faster cell detection . 37 Fig. 3.7 Pipette Detection 40 Fig. 3.8 Y-axis Coordination . 41 Fig. 3.9 Tip Focalization . 42 Fig. 3.10 Value of Entropy 43 Fig. 3.11 Penetration . 44 Fig. 4.1 A CNC Machine and workshop . 51 Fig. 4.2 Sensor board and antenna board 52 Fig. 4.3 DFDS control structure 52 Fig. 4.4 Algorithm flow chart . 53 IV Fig. 4.5 Fault detection with SS=1200 rpm, fr =300 mm/min, depth of cut=1 mm . 58 Fig. 4.6 Overall System Configuration . 60 Fig. 4.7 Vision-assisted Servo System 61 Fig. 4.8 Mounting of the Infrared Thermometer . 62 Fig. 4.9 Process Flowchart 64 Fig. 4.10 Moving Object Extraction . 67 Fig. 4.11 Thermal devices . 69 Fig. 4.12 Control System Structure . 70 Fig. 4.13 Maximum speed permissible . 75 Fig. 4.14 Calculation of minimum and maximum speed 76 Fig. 4.15 Step response with PID control . 78 Fig. 4.16 Controller response and tracking error 79 Fig. 4.17 Simulation Scene . 80 Fig. 4.18 Temperature measurement during simulation . 81 Fig. 4.19 Temperature measurement in real experiment . 82 Fig. 4.20 Explanation of sudden temperature raise . 83 Fig. 4.21 Accuracy testing using thermal camera . 84 V List of Tables Table 2.1 Recognition Results 24 Table 3.1 Comparison of Experimental Result . 46 VI List of Abbreviations CCD Charge-Coupled Device CNC Computer Numerical Control CT Computerized Tomography ECG Electrocardiogram EEG Electroencephalography DFDS Distributed Fault Detection System HCDA Hough Cell Detection Algorithm FCDA Fast Cell Detection Algorithm FD Frame Difference LQR Linear Quadratic Regulator MRI Magnetic Resonance Imaging OCR Optical Character Recognition RGB Red, Green, Blue VII Summary The rapid advancement of the microprocessor, the perpetually declining cost of electronic devices as well as the increasing availability of handheld equipment for digitizing and displaying images have strongly spurred the continued growth for computer imaging technologies. Other impetus for such development stems from a steady flow of new applications, such as commercial, industrial and medical applications. This trend generates ample opportunities for the development of new image and vision based applications. This thesis addresses different sets of challenges present in different applications of image and visionbased systems. It presents the design of three image and vision-based systems which can be used in different and diverse arenas: mobile and digital devices, biomanipulation systems and CNC machine surveillance. Through investigation in these diverse areas, the different challenges facing image processing & vision systems are better appreciated. Mobile applications are rampantly available nowadays for a variety of purposes. The small and inexpensive wearable devices facilitate new ways through which users can interact with the physical world. Multimedia functions are fast expending and reshaping the growth of the market for phone developers. In the first part of the thesis, a human-machine interactive software has been developed which could be embedded in a mobile or digital device to extract the text from scene images and translate into other languages. Text extraction is mainly based on the color and edge information of characters. A fast yet efficient OCR engine is also designed to translate the extracted text using template VIII deployed in the coastal region to monitor the environment in a real-time manner. Such device can be dived into the ocean to monitor the situation of the ocean surface. The key part of this device is the algorithm in the image processor. If waste was dumped on the surface of the ocean (e.g, a bottle), the algorithm shall be able to detect and localize it. If oil was spilled on the ocean, the transparency of the water would be quite different since the oil blocks the sunshine. 91 Author’s Publications Journal Publications: Y. Zhang and K. K. Tan, “Text extraction from images captured via mobile and digital devices”, International Journal of Computational Vision and Robotics, 010102. Y. Zhang, K. K. Tan, S. Huang, "Vision-Servo System for Automated Cell Injection," IEEE Trans. on Industrial Electronics, vol. 56, no. 1, pp. 231-238, Jan 2009. K. K. Tan, S.N. Huang, Y. Zhang, “Distributed Fault Detection System Based on Sensor Wireless Network”, Journal of Computer Standards and Interfaces, Vol. 31, Issue 3, March 2009, Pages 573-578. Y. Zhang, S. Huang, K. K. Tan, “Decoupled Tracking and Thermal Monitoring of Non-Stationary Targets”, ISA Transactions, accepted, 2009. Conference Publications: Y. Zhang and K. K. Tan, “Text Extraction from Images Captured via Mobile and Digital Devices,” Fifth International Conference on Industrial Automation, Montreal, TSTI-07, 2007. Zhang, Y.; Tan, K.K.; Huang, S., “Software Based Vision System for Automated Cell Injection”, BioMedical Engineering and Informatics, 2008. BMEI 2008. 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Syst., Man, Cybern., Nashville, TN, Oct. 2000, pp. 1592–1597. 106 [...]... the applications that require the recognition and counting of certain types of cells The field of law enforcement and personal identification is another active area for computer vision system development, with applications ranging from automatic identification of 3 fingerprints and vein to facial and retinal recognition Currently, vision systems are placed on the streets to take pictures of speeders and. .. diagnosis and medical education, which includes Magnetic Resonance Imaging (MRI), Computerized Tomography (CT), Radiography, Electrocardiogram (ECG) and Electroencephalography (EEG) etc With the rapid development of computer and image technology and the increasing mature of picture and image technology, this technology has gradually entered medical field and improved the quality of medical images and vision. .. developing image and vision systems for different application areas with different sets of challenges Text extraction and translation software for mobile and digital devices, vision based control strategies for biomanipulation and industrial surveillance system 1.2.1 Text Extraction and Translation Images play a very important role in information storage and delivery An efficient text extraction and recognition... of processing, or require access and use of a large database of information Computer vision systems are used in many and various types of environments-from manufacturing plants to hospital surgical suites to the surface of Mars The most important task of computer vision system is automated visual inspection (AVI) [11], which can be used for the purpose of measurements, gauging, integrity checking and. .. identifies and sorts of the different parts Computer vision systems are also used in many different areas within the medical and pharmacological community, with the only certainty being that the types of applications will continue to grow Current examples of medical systems being developed include: systems to diagnose skin tumors automatically [23], systems to aid neurosurgeons during brain surgery, systems. .. upon by a computer Although people are involved in the development of the system, the final application requires a computer to use the visual information directly One of the major topics within the field of computer vision is image analysis The field of computer vision may be best understood by considering different types of applications Many of these applications involve tasks that either are tedious... the vision based surveillance system in industrial applications In the first part of the thesis, a review on conventional techniques used in monitoring system is made along with a discussion of their limitations and drawbacks Special attention is placed on the image processing and predictive control system design Practical issues have been discussed in terms of maximum and minimum speed permissible and. .. other Image Processing: Image processing is a form of computer imaging where the application involves a human being in the visual loop [68] In other words, the images are to be examined and acted upon by people Major application fields of image processing include medical imaging [99] and astronomical observation Medical 1 imaging has grown over the last decade to become an essential component of diagnosis... speeders and in the future, computer vision systems may be used to manipulate the whole transportation systems in an automatic and intelligent way Another term which has similar meaning as computer vision is machine vision [10] Machine vision is concerned with the engineering of integrated mechanical-optical-electronic-software systems for examining natural objects and materials Although it uses similar... information Abnormal objects and noise will be eliminated based on a predefined criterion The binary image will be sent to an OCR engine for recognition Final translation result will be generated with the help of a database The effectiveness of the proposed algorithm in meeting the challenges behind the processing of such images will be highlighted with real images 1.2.2 Vision- based Automatic Cell . Development of Image Processing and Vision Systems with Industrial Applications Zhang Yi A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL AND. image and vision based applications. This thesis addresses different sets of challenges present in different applications of image and vision- based systems. It presents the design of three image. (EEG) etc. With the rapid development of computer and image technology and the increasing mature of picture and image technology, this technology has gradually entered medical field and improved