Image Acquisition System based on Synchronized High Resolution Gigabit Ethernet Cameras

Over the last few years, the huge rise in various computer vision applications can be observed. They are widely used in such areas like video surveillance, medical diagnostics, biometrics recognition, the automotive or military industries. Most of these solutions take advantage of high-resolution cameras in order to obtain high quality images. Surprisingly, little attention is paid in the literature to the practical implementation of off-the-shelf image acquisition systems. Most available solutions are composed of custom developed electronic devices which use specialized multi-core DSPs and / or FPGA technology. Therefore, in this paper the novel realization of the scalable and comprehensive image acquisition system based on synchronized high resolution Gigabit Ethernet cameras is presented. The proposed solution allows the connection of multiple cameras together with any number of external illumination modules. Selected devices can be synchronized with each other in user-defined configurations. Hence, designed solution can be easily integrated in both simple and complex applications. Authors describe in detail design and implementation processes of the proposed platform. The performance issues that can occur in such systems are presented and discussed. Obtained results are encouraging and useful for the development of similar solutions.

[1]  Henrique S. Malvar,et al.  High-quality linear interpolation for demosaicing of Bayer-patterned color images , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  Josephine Sullivan,et al.  One millisecond face alignment with an ensemble of regression trees , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Ito Takahiro,et al.  Histogram of oriented gradients for human detection in video , 2018, 2018 5th International Conference on Business and Industrial Research (ICBIR).

[4]  Du Xu,et al.  High precision time synchronization scheme for Distributed Intrusion Detection System , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

[5]  Dmitry Namiot,et al.  On micro-services architecture , 2014 .

[6]  Masatoshi Ishikawa,et al.  Frame synchronization for networked high-speed vision systems , 2014, IEEE SENSORS 2014 Proceedings.

[7]  Miti Ruchanurucks,et al.  Automatic landing assistant system based on stripe lines on runway using computer vision , 2015, 2015 International Conference on Science and Technology (TICST).

[8]  Anil K. Jain,et al.  Periocular biometrics in the visible spectrum: A feasibility study , 2009, 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems.

[9]  Masatoshi Ishikawa,et al.  High-speed gaze controller for millisecond-order pan/tilt camera , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  João Pedro Barreto,et al.  A New Solution for Camera Calibration and Real-Time Image Distortion Correction in Medical Endoscopy–Initial Technical Evaluation , 2012, IEEE Transactions on Biomedical Engineering.

[11]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[12]  Omar Faruque Sarker,et al.  Flexible communication in multi-robotic control system using head: Hybrid event-driven architecture on D-Bus , 2010 .

[13]  Lei Zhang,et al.  Image demosaicing: a systematic survey , 2008, Electronic Imaging.

[14]  Damian Kacperski,et al.  Calibration of vision systems operating in separate coordinate systems , 2016 .

[15]  Sabri M. A. A. Ahmed,et al.  Vision-Based Detection and Tracking of Moving Target in Video Surveillance , 2014, 2014 International Conference on Computer and Communication Engineering.

[16]  Sinisa Segvic,et al.  Experimental Evaluation of Autonomous Driving Based on Visual Memory and Image-Based Visual Servoing , 2011, IEEE Transactions on Intelligent Transportation Systems.

[17]  Xin He,et al.  The design of high speed image acquisition system over Gigabit Ethernet , 2010, 2010 IEEE International Conference on Wireless Communications, Networking and Information Security.

[18]  Rob Aspin,et al.  Synchronization of Images from Multiple Cameras to Reconstruct a Moving Human , 2010, 2010 IEEE/ACM 14th International Symposium on Distributed Simulation and Real Time Applications.

[19]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[20]  Brian S. R. Armstrong,et al.  Soft Synchronization: Synchronization for Network-Connected Machine Vision Systems , 2007, IEEE Transactions on Industrial Informatics.

[21]  Damian Kacperski,et al.  Pose-oriented face images acquisition platform , 2016, 2016 MIXDES - 23rd International Conference Mixed Design of Integrated Circuits and Systems.

[22]  Lu Lin,et al.  Images acquisition and processing system based on CIS and DSP , 2013, 2013 IEEE International Conference on Information and Automation (ICIA).

[23]  Anil K. Jain,et al.  PTZ camera assisted face acquisition, tracking & recognition , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[24]  Davis E. King Max-Margin Object Detection , 2015, ArXiv.

[25]  Arun Ross,et al.  Periocular Biometrics in the Visible Spectrum , 2011, IEEE Transactions on Information Forensics and Security.