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  • Fuzzy image processing technology in the security field

        With the rapid development of computer image processing technology, information and popularity increased, and people´s security awareness, real-time video surveillance system has gradually become an integral part of people´s lives, has been widely used in the production, transport, social security and other aspects. But due to bad weather (fog, rain, wind, light, etc.) and monitoring the system´s own technical constraints, the video images tend to reach the desired effect. Figure quality degraded or blurred, leading to cause difficulties to the identification, evidence collection, and event analysis operation, the system can not be normal application. Therefore, the fuzzy image processing technology research and application in the field of security is very important.
        Analysis of causes of blurred images
        Of the system itself
        An all-analog monitoring system, front-to back-end image capture, image transfer, image storage, image display several aspects of composition. In each session, or will produce a loss of video information, that is, the image quality deterioration or blur.
        Lens: influence into the luminous flux of the camera and imaging accuracy, will directly lead to image blurring; camera sensor Sensor: impact on the optical signal acquisition and the photoelectric conversion effect, will directly result in blurred images; video transmission cable BNC connectors at both ends: Due to signal shielding the gap will cause signal loss and video transmission cable through long-distance transmission, the resistance of the transmission cable, shielded, impedance matching and other issues will cause signal attenuation, and also a direct result of poor image quality blur monitor image showing side there will be some signal loss.
        A full digital video surveillance systems, network transmission, the encoded digital video signal transmission and storage for the analog system can more effectively avoid signal attenuation caused by the image damage. However, when the lens, image acquisition and back-end rendering image signal loss is still unavoidable. In addition, digital video surveillance system video signal A / D conversion, video encoding compression link, these sectors will lead to the loss of image information. Existing video compression algorithm is lossy compression, will directly lead to the loss of video information to affect the video clarity.
        The natural environment
        In addition to the factors of the system itself, the natural environment also has great influence on the video image clarity. When the wind, rain, snow, fog and other natural weather, will result in dramatically decreased or blurred image quality. In addition, there is insufficient illumination, backlighting, backlit, the temperature is too low or too high, etc., will impact on the image to restore the system that affects the sharpness of the image. Sensor imaging in low-light conditions, the camera will produce a lot of noise, the noise will affect the sharpness of the image, and make the image coded stream is a substantial increase.
        Man-made environment
        The power supply system is not "clean", that is, fleeing into the relatively strong interference signal, specifically refers to the interference signal superimposed on the 50Hz sine wave, if the grid power SCR FM speeder, SCR rectifier, thyristor AC-DC conversion device and so will power to cause pollution.
        TV monitoring system near strong sources of electromagnetic interference or electromagnetic radiation. Electromagnetic interference sources such as welding, radio transmitters, large motor, the relay interference can lead to interference with the video signal. Electromagnetic interference can cause the image equally spaced bars or images regularly flashing stripes, etc., resulting in blurred images. There is man-made destruction lead to, for example, have been made difficult to identify the license plate, etc., resulting in the camera can not intake the license plate number, etc..
        Fuzzy image processing technology development
        Since the 1990s, the security industry has experienced a period of rapid development. With the development of the security monitoring system from the all-analog to all-digital, people increasingly high demand for image quality, image resolution has also experienced changes from CIF to SD and then HD.
        Early monitoring system uses the analog signal transmission, called the first generation of analog monitor the times when the video file through the tape recorder to record and save. Because the storage of video images are analog devices, analog storage device with the extension of the use of time, the image there will be some loss of information. Fuzzy image processing technology based on digital image processing technology, so in the era of pure analog, has not yet been introduced to the field of security.
        As computer technology continues to evolve due to the inherent defects of the analog control system, digital storage gradually replaced analog tape storage. Followed them into the second generation of quasi-digital surveillance system-based Digital Video Recorder DVR to replace the analog VCR, taken the first step in digital surveillance. After digitization of the video image, the image processing technology began to come in handy, fuzzy image processing technology is gradually being introduced to the field of security.
        With the development of computer and network technology, video surveillance has been developed to the era of all-digital IP-based network monitoring, so into the third-generation all-digital network video surveillance camera era. The product of this era on behalf of the IPC, NVR. After the digital video images, fuzzy image processing technology in the field of security has been widely used.
        Fuzzy image processing technology is a kind of image processing technology, the use of computers, computing or processing the image information in the digital signal, in order to improve the quality of the image, so that to achieve the desired results, also known as a computer image processing technology. Weak image information such as noise pollution image to remove noise, enhance handling, such as geometric correction of image distortion. In recent years, with people getting higher and higher awareness of security and social security needs of more and more intense monitoring of image processing technology will also continue to evolve in this market demand and the law, and play a more and more visible role.
        The special requirements of the Security Industry
        The computer image processing the image signals into digital signals and use the computer to process it. Due to the fast processing speed of the computer, and digital signal with low distortion, easy save, easy to transport, anti-interference ability, thus a wide range of applications of computer image processing, including aerospace, remote sensing, medical devices, industrial automation, detection major areas of security identification. Each application domain has its special requirements, also has its inherent particularity in the security surveillance industry applications:
        A higher image clarity. Monitoring site in the law and order, public security organs often require video surveillance to identify suspects, evidence, and generally not high-definition video to reach such a request. Traffic monitoring site, the traffic police by monitoring the image to identify the license plate violations, and driver requirements, fuzzy images simply can not be applied on such occasions.
        2, the monitoring of different industries with differences in the image requirements. Such as medical monitoring, reducing the image´s color requirements are relatively high. Intelligent traffic surveillance camera night illumination and capture speed requirements, the requirements can clearly distinguish the license plate. Long-term stability in unsupervised conditions in unmanned surveillance equipment.
        Outdoor installation, unattended. In the field of security, in most cases equipment needs to be installed outdoors, the equipment needs to withstand years of wind and sun. Electronic equipment, the speed of aging will be faster than other areas. The aging of the camera, lens, transmission lines and other facilities will lead to increasingly blurred image.
        4, massive video large ones. Large Safe City surveillance project, video large ones will reach tens of thousands of road, or even more. Look forward to the video encoding bitrate compression ratio of the highest in the field of video surveillance, thus reducing bandwidth and storage capacity requirements. This leads to more loss of information in the link of the video encoding, resulting in blurred images.
        These special applications in the field of security will lead to a decline in image clarity, in turn, high demands will inevitably lead to fuzzy image processing technology has broad application prospects in the image clarity.
        Limitations of the fuzzy image processing technology
        By the level of hardware technology, the transmission bandwidth, as well as environmental factors such as image blurring problem can not be completely resolved.
        To display images from the collection, transmission, storage, and any aspects of image quality are critical, any step of the problem will affect the image quality, and this effect is irreversible. So, completely resolve the image blurring problem that needs a full range of technical updates. For example, in the context of the current digital imaging technology, the coding technique is one of the bottlenecks affecting the image quality, if there is a high compression ratio, image small loss of coding algorithm, of course, to a certain extent to solve the compression caused by image blurring , but this algorithm is effective, and usually require a higher operating cost, so you need hardware updates to this algorithm.
        Similar to the super-resolution reconstruction of blurred image processing technology, due to the complexity of the algorithm, the conventional equipment is difficult to do real-time processing high-definition images, so the efficiency of the algorithm is still fuzzy image processing, one of the reasons, which need to start from the algorithm and hardware to improve the efficiency of the algorithm, but also need to upgrade the hardware performance.
        In addition, the solution to a variety of fuzzy image processing algorithms are based on a particular scene applications generated the locality and the limitations of various algorithms have caused the obstacles of the algorithm is applied. So in the future for many years, the image processing algorithms and models still have a long way to go.
        Trends and outlook
        Broadly speaking, for less than adequate information of the image can be called fuzzy image, the image blurring problem with the enhancement of people´s needs and have new manifestations. Such as monitoring areas may only need a certain resolution image needs to meet face recognition with the development of society, perhaps we need a video to analyze a person´s mouth movements to analyze his what to say, this will need a clearer image of higher resolution. This will be an eternal pursuit of the same direction, so the fuzzy image processing problems will be has been studying down.
        Video surveillance as part of the Internet of Things, with the continuous development and application of Things, and ultimately will toward intelligent direction, the automatic analysis of images blurred to become a system self-test applications, intelligent analysis, the system will will automatically identify the image of the geometry, color, noise, blur, integration, and super-resolution image effects for automatic analysis and processing. With the more extensive scope of application of fuzzy image processing technology, fuzzy image processing technology and the perfect combination of intelligent analysis will inevitably become a trend.

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