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A Novel Image Encoding and Communication Technique of B/W Images for IOT, Robotics and Drones using (15, 11) Reed Solomon Scheme

机译:使用(15,11)Reed Solomon方案的IOT,机器人和无人机的B / W图像的新颖图像编码和通信技术

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In the modern age of IOT and Robotics, different intelligent entities like robots, drones, IOT nodes or smart vehicles need fast and error-free communication of data, which is predominantly in the form of images. The medium used for communication of this data is mainly wireless and it can be short distance, medium distance, long haul or even satellite links crossing the ionosphere layers. Different wireless mediums incorporate different types of noises in the images being transmitted by Drones. Robots or IOT Nodes. For better analysis and then performing subsequent action on the basis of these received images using artificial intelligence, machine learning or machine vision, it is imperative that the images transmitted are encoded and recovered as fast and as error-free as possible. Normal conventional methods use different image correction algorithms for detection and correction of errors in images. Reed Solomon codes, which are normally used for error detection and correction at data link layer in TCP/IP protocol stack, have a high probability of signal correction and are highly efficient due to their burst error detection and correction capabilities. The RS codes can be implemented where there is a large number of input symbols and noise duration is relatively small as compared to the code word. Sometimes at the receiver end, we get images which are partially corrupted and only half or some part of them is visible. Most of the filters used for image reconstruction insert the approximated bits in place of the corrupted bits by using some algorithms but if only partial part of the image is corrupted, no filter will be able to recover the images property as it will also change the bits in the non-corrupted part of the image. We have proposed a novel approach of using RS codes for the detection and correction of errors in the images. This novel technique can be used over a variety of applications including robotics, drones, IOT nodes, smart vehicles using wireless and satellite communication, which include the transfer of images and decision making on the basis of the content of the images.
机译:在现代的IOT和机器人,不同的智能实体,如机器人,无人机,物联网节点或智能车辆需要快速和无差错的数据通信,这主要以图像的形式。用于通信此数据的介质主要是无线的,它可以是短距离,中距离,长途甚至穿过电离层层的卫星链路。不同的无线介质在由无人机传输的图像中包含不同类型的噪声。机器人或物联网节点。为了更好地分析,然后根据这些接收的图像使用人工智能,机器学习或机器视觉执行后续动作,因此必须快速地编码并恢复传输的图像并尽可能快地恢复。正常的传统方法使用不同的图像校正算法进行检测和校正图像中的错误。 REED所罗门代码通常用于TCP / IP协议栈中数据链路层的错误检测和校正,具有高概率的信号校正,并且由于其突发错误检测和校正能力而具有高效。可以实现RS代码,其中大量输入符号和与代码字相比相对较小的噪声持续时间。有时在接收器结束时,我们得到部分损坏的图像,只能看到它们的一半或部分部分。大多数用于图像重建的过滤器都将近似位代替使用某些算法来代替损坏的位,但如果只有图像的部分部分已损坏,则不会滤波器将能够恢复图像属性,因为它也会更改图像属性在图像的非损坏部分。我们提出了一种使用RS代码的新方法,用于检测和校正图像中的错误。这种新颖的技术可用于包括机器人,无人机,物联网节点,使用无线和卫星通信的智能车辆的各种应用,包括基于图像的内容的图像和决策的转移。

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