Real-Time Vision System for License Plate Detection and Recognition on FPGA

Rapid development of the Field Programmable Gate Array (FPGA) offers an alternative way to provide acceleration for computationally intensive tasks such as digital signal and image processing. Its ability to perform parallel processing shows the potential in implementing a high speed vision system. Out of numerous applications of computer vision, this paper focuses on the hardware implementation of one that is commercially known as Automatic Number Plate Recognition (ANPR).Morphological operations and Optical Character Recognition (OCR) algorithms have been implemented on a Xilinx Zynq-7000 All-Programmable SoC to realize the functions of an ANPR system. Test results have shown that the designed and implemented processing pipeline that consumed 63 % of the logic resources is capable of delivering the results with relatively low error rate. Most importantly, the computation time satisfies the real-time requirement for many ANPR applications

Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system

Automatic number plate recognition (ANPR) systems are becoming vital for safety and security purposes. Typical ANPR systems are based on three stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). Recently, high definition (HD) cameras have been used to improve their recognition rates. In this paper, four algorithms are proposed for the OCR stage of a real-time HD ANPR system. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. All proposed algorithms have been implemented using MATLAB as a proof of concept and the best one has been selected for hardware implementation using a heterogeneous system on chip (SoC) platform. The selected platform is the Xilinx Zynq-7000 All Programmable SoC, which consists of an ARM processor and programmable logic. Obtained hardware implementation results have shown that the proposed system can recognize one character in 0.63 ms, with an accuracy of 99.5% while utilizing around 6% of the programmable logic resources. In addition, the use of the heterogenous SoC consumes 36 W which is equivalent to saving around 80% of the energy consumed by the PC used in this work, whereas it is smaller in size by 95%

IMPROVED LICENSE PLATE LOCALIZATION ALGORITHM BASED ON MORPHOLOGICAL OPERATIONS

Automatic License Plate Recognition (ALPR) systems have become an important tool to track stolen cars, access control, and monitor traffic. ALPR system consists of locating the license plate in an image, followed by character detection and recognition. Since the license plate can exist anywhere within an image, localization is the most important part of ALPR and requires greater processing time. Most ALPR systems are computationally intensive and require a high-performance computer. The proposed algorithm differs significantly from those utilized in previous ALPR technologies by offering a fast algorithm, composed of structural elements which more precisely conducts morphological operations within an image, and can be implemented in portable devices with low computation capabilities. The proposed algorithm is able to accurately detect and differentiate license plates in complex images. This method was first tested through MATLAB with an on-line public database of Greek license plates which is a popular benchmark used in previous works. The proposed algorithm was 100% accurate in all clear images, and achieved 98.45% accuracy when using the entire database which included complex backgrounds and license plates obscured by shadow and dirt. Second, the efficiency of the algorithm was tested in devices with low computational processing power, by translating the code to Python, and was 300% faster than previous work

MLP neural network based gas classification system on Zynq SoC

Systems based on Wireless Gas Sensor Networks (WGSN) offer a powerful tool to observe and analyse data in complex environments over long monitoring periods. Since the reliability of sensors is very important in those systems, gas classification is a critical process within the gas safety precautions. A gas classification system has to react fast in order to take essential actions in case of fault detection. This paper proposes a low latency real-time gas classification service system, which uses a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) to detect and classify the gas sensor data. An accurate MLP is developed to work with the data set obtained from an array of tin oxide (SnO2) gas sensor, based on convex Micro hotplates (MHP). The overall system acquires the gas sensor data through RFID, and processes the sensor data with the proposed MLP classifier implemented on a System on Chip (SoC) platform from Xilinx. Hardware implementation of the classifier is optimized to achieve very low latency for real-time application. The proposed architecture has been implemented on a ZYNQ SoC using fixed-point format and achieved results have shown that an accuracy of 97.4% has been obtained

Development of Automatic Digitization of Truck Number in Open Cast Mines Using Microcontroller

Geological condition in mines appears to be extremely complicated and there are many intelligence security problems. Production is falsely transfer by the unauthorized truck from mine pits also at loading point. It also lifted in wrong ways by malfunctioning of the truck weight in Weigh Bridge. Mining organizations are under the control of mafia and countless can be added to the mines mafia. An intelligence security system is need to monitor truck number in automatically using image acquisition method, automatic detection, recognition process, communication technology, information technology and microcontroller innovation to understand the working specification of the mining region. Tracking of the number plate from the truck is an important task, which demands intelligent solution. Intelligent surveillance in open casts mine security network using data accession is a prime task that protects the secure production of mines. So automatic truck number recognition technique is used to recognize the registration number of the truck which is used for transferring the mine production as well as track record the amount of the production. It also preserves the mines and thus improving its security. For extraction and recognition of number plate from truck image the system is uses MATLAB software tool. It is assumed that images of the truck have been captured from digital camera. The data acquisition terminal uses the PIC16F877A microcontroller as a core chip for sending data. The data are communicated through USB to TTL converter (RS232) with the main circuit to realize intelligent monitoring. To store the data in permanently it is uses EEPROM chip. Alphanumeric Characters on plate has been extracted and recognized using template images of alphanumeric characters. The proposed system performs the real time data monitoring to recognize the registration number plate of the trucks for getting required important information. It also provides to maintenance the history of data and support access contro

Space station data system analysis/architecture study. Task 2: Options development DR-5. Volume 1: Technology options

The second task in the Space Station Data System (SSDS) Analysis/Architecture Study is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This volume identifies the preferred options in the technology category and characterizes these options with respect to performance attributes, constraints, cost, and risk. The technology category includes advanced materials, processes, and techniques that can be used to enhance the implementation of SSDS design structures. The specific areas discussed are mass storage, including space and round on-line storage and off-line storage; man/machine interface; data processing hardware, including flight computers and advanced/fault tolerant computer architectures; and software, including data compression algorithms, on-board high level languages, and software tools. Also discussed are artificial intelligence applications and hard-wire communications

RFID Based Toll Booth Management System using Internet of Things

Automation has played a vital role in the advancement of engineering and science. In recent times, traffic congestion on toll booths has been increasing day by day in countries like Pakistan. In such circumstances, there is a need to upgrade the Toll Booth Management System. A proper gate system is required to install on many organizations and institutions, which are being controlled manually by a security person. This process results in long queues of vehicles at gates, thus taking too much time and results in burning extra fuel of the vehicles. The system is still not secure. In this paper, the idea of making surveillance smart toll booth system that depends on Radio Frequency Identification (RFID) Innovation and online database has been presented. The automated gate system should be installed at every toll booth as a solution to this. After scanning the RFID, the system allows the vehicle to pass through the gate if data is present at the database. Otherwise, the automobile has to get approval from higher authorities. The developed system scans the RFID tag using RFID reader and compares it with database for authentication purposes and then automatically lifts the barrier up if that vehicle is permissible

Development of a real-time ultrasonic sensing system for automated and robotic welding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The implementation of robotic technology into welding processes is made difficult by the inherent process variables of part location, fit up, orientation and repeatability. Considering these aspects, to ensure weld reproducibility consistency and quality, advanced adaptive control techniques are essential. These involve not only the development of adequate sensors for seam tracking and joint recognition but also developments of overall machines with a level of artificial intelligence sufficient for automated welding. The development of such a prototype system which utilizes a manipulator arm, ultrasonic sensors and a transistorised welding power source is outlined. This system incorporates three essential aspects. It locates and tracks the welding seam ensuring correct positioning of the welding head relatively to the joint preparation. Additionally, it monitors the joint profile of the molten weld pool and modifies the relevant heat input parameters ensuring consistent penetration, joint filling and acceptable weld bead shape. Finally, it makes use of both the above information to reconstruct three-dimensional images of the weld pool silhouettes providing in-process inspection capabilities of the welded joints. Welding process control strategies have been incorporated into the system based on quantitative relationships between input parameters and weld bead shape configuration allowing real-time decisions to be made during the process of welding, without the need for operation intervention.British Technology Group (BTG

Data Acquisition System For Fingerprint Ultrasonic Imaging Device

Ultrasonic imaging of fingerprint is relatively new application in the field of Biometrics that is capable of obtaining fingerprint pattern for identification purposes. In previous digital data acquisition system, image of the skin-plate contact pattern have been produced. Unfortunately, these systems do not provide any information about in-depth structure of the fingerprint area. In this work, data acquisition system for ultrasonic imaging of fingerprint was developed with in-depth imaging capability. In this system finger is inserted into a hollow cylinder and set of rotating focused ultrasonic transducers scans over the finger. Emitting and receiving of ultrasonic signal is realized by the DSP-based data acquisition board. Software controls scanner motion, obtains data and transfer it into computer in the form of three-dimension digital data cube. Software is capable to store 3D acoustical image of fingerprints and visually represent it in the form of C-Scan, B-Scan and A-Scan