A brief experience on journey through hardware developments for image processing and it’s applications on Cryptography
Sangeet Saha1, Chandrajit pal2, Rourab paul3, Satyabrata Maity 4, Suman Sau5 Dept of Computer Science & Engineering 1, A. K. Choudhury School of Information Technology2,3,4,5 University Of Calcutta, Kolkata, India
92, A.P.C Road,Kolkata-700009
[Sangeet.saha87, palchandrajit, rourab.paul, satyabrata.maity, sumansau] @gmail.com
Image processing, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit(ASIC) , Digital Signal Processor(DSP) image thresholding, Security ,RC4
The importance of embedded applications on image and video processing, communication and cryptography domain has been taking a larger space in current research era. Improvement of pictorial information for betterment of human perception like deblurring, de-noising in several fields such as satellite imaging, medical imaging etc are renewed research thrust. Specifically we would like to elaborate our experience on the significance of computer vision as one of the domains where hardware implemented algorithms perform far better than those implemented through software. So far embedded design engineers have successfully implemented their designs by means of Application Specific Integrated Circuits (ASICs) and/or Digital Signal Processors (DSP), however with the advancement of VLSI technology a very powerful hardware device namely the Field Programmable Gate Array (FPGA) combining the key advantages of ASICs and DSPs was developed which have the possibility of reprogramming making them a very attractive device for rapid prototyping. Communication of image and video data in multiple FPGA is no longer far away from the thrust of secured transmission among them, and then the relevance of cryptography is indeed unavoidable. This paper shows how the Xilinx hardware development platform as well Mathwork’s Matlab can be used to develop hardware based computer vision algorithms and its corresponding crypto transmission channel between multiple FPGA platform from a system level approach, making it favourable for developing a hardware-software co-design environment.
Vision processing incorporates human perception and intelligence which makes the field most interesting to the research community as it can mimic human behaviour in the computer system by means of video surveillance system, integrating more intelligence to machines such as robots, as well as in ecology, biometrics and medical applications. Interestingly, recent NASA’s mission “Curiosity” on Mars, sending valuable images and information of Mars environment in a secure communication channel, transmitted images also need to processed exhaustively to find out any vital information about Mars.
Hardware designs for image and video processing is used for faster performance rather than software, to meet the requirements of the end users, keeping its market relevancy and at the same time security is another concern, so the necessity to communicate these media data securely among multiple platforms after processing to enhance human perception and satisfaction in which our focus lies.
The basic 4 steps in image processing domain are pre-processing, segmentation, feature extraction and recognition  and those has been keeping their strong importance in research mostly in the case of software implementation and very few implemented on hardware. Initial pre-processing step is carried out to enhance the quality of the original image by removing noise, unbalanced brightness etc as common interfering elements followed by segmentation where images are separated from the background into various elements with properties. Next in the feature extraction stage, extraction is performed on every detected object to reduce its information to a list of parameters storing in memory. Finally in the recognition stage a set of signals are generated...