Evaluation of a Seamless Surveillance Video Monitoring System Used by High-Speed Network and High-Resolution Omni-directional Cameras

Author(s):  
Takuma Kon ◽  
Noriki Uchida ◽  
Koji Hashimoto ◽  
Yoshitaka Shibata
2011 ◽  
Vol 291-294 ◽  
pp. 2823-2828
Author(s):  
Jin Qing Liu ◽  
Qun Zhen Fan

This paper adopts high-speed fixed-point signal processor TMS320DM64 produced by TI company, XC2S150 chip FPGA produced by Xilinx company, video front-end decoder chip SAA7111 and back-end encoding chip AL250 new launched by PHILIP company, which constituted a high-speed, intelligent live video monitoring system. The system video image transmission of strong real-time, high efficiency and good transmission quality can meet the requirements of many video image processing and transmission field application in current, and has a good application prospect. The design of system software and hardware that introduced in this paper is the key.


2020 ◽  
Author(s):  
Ramesh Madipally ◽  
Sheela Nair L ◽  
Rui Taborda

<p>In recent years, Coastal video monitoring methods have been widely accepted tools for continuous monitoring of complex coastal processes. In this paper, the progress made on a new python based coastal video monitoring system, PI-COSMOS (Portuguese Indian COaStal MOnitoring System) which is being developed and tested jointly in India and Portuguese coasts is presented. PI-COSMOS system aims at providing open source, high speed video monitoring toolboxes for the coastal community that can be used anywhere in the world. PI-COSMOS is camera independent system and comprises four modules viz. PI-Calib for camera calibration, RectiPI for video imagery rectification, PI-ImageStacks for image product and pixel product generation and PI- DB for efficient database management. The applicability of PICOSMOS system under different coastal environment conditions has been tested using the data collected from the India as well as the Portugal coast. The results from one of the Indian stations installed at Kozhikode beach, Kerala, India situated at 11°15'14.12" N, 75° 46'15.40" E are presented here to demonstrate the capabilities of the newly developed PI-COSMOS system. the performance of PI-COSMOS is evaluated by conducting a comparative study among PICOSMOS and existing video monitoring toolboxes like UAV processing toolbox provided by Coastal Research Imaging Network and RectifyExtreme provided by the University of Lisbon and it is found that the processing speed of PI-COSMOS is very much high i.e. more than 5 times when compared to UAV processing toolbox and RectifyExtreme.  The high speed performance, camera independent nature and easiness in the operation made PI-COSMOS as the simplest and advanced open source video monitoring system.</p><p> </p>


Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.


Author(s):  
I Made Oka Widyantara ◽  
I Made Dwi Asana Putra ◽  
Ida Bagus Putu Adnyana

This paper intends to explain the development of Coastal Video Monitoring System (CoViMoS) with the main characteristics including low-cost and easy implementation. CoViMoS characteristics have been realized using the device IP camera for video image acquisition, and development of software applications with the main features including detection of shoreline and it changes are automatically. This capability was based on segmentation and classification techniques based on data mining. Detection of shoreline is done by segmenting a video image of the beach, to get a cluster of objects, namely land, sea and sky, using Self Organizing Map (SOM) algorithms. The mechanism of classification is done using K-Nearest Neighbor (K-NN) algorithms to provide the class labels to objects that have been generated on the segmentation process. Furthermore, the classification of land used as a reference object in the detection of costline. Implementation CoViMoS system for monitoring systems in Cucukan Beach, Gianyar regency, have shown that the developed system is able to detect the shoreline and its changes automatically.


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