ABSTRACT: With the rise of the electricity industry, to the logistics sorting industry caused great pressure to design a PLC (programmable logic controller) based on control, combined with Kingview software, and the application of bar code recognition technology, automaticidentification and sorting system. According to the structure of the system, the working principle of the system is analyzed, the control requirements are put forward, and the hardware design, software design and configuration process design of the control system are carried out. Using PLC as the next bit machine to improve the acquisition signal and control signal accuracy, and can be based on functional requirements on-site modification and commissioning procedures at the same time easy maintenance. Application configuration Wang as the host configuration software, users can easily adapt to their own needs to adapt to the data acquisition system, real-time monitoring system operating status, protection of information flow, very consistent with the needs of modern production.
Abstract: Automatic License Plate Recognition (ANPR) is an image processing technology that uses a license plate to identify the vehicle. The goal is to design an efficient automated vehicle identification system using the vehicle license plate. The system is implemented at the entrance of the security control of a highly restricted area, such as the military zones or the area around the main government offices, for example. Parliament, Supreme Court, etc. The developed system spots the vehicle and then captures the vehicle image. The region of the vehicle's plate is extracted using the segmentation of the image into an image. The optical character recognition technique is used for character recognition. The resulting data is used to compare it with records in a database for specific information such as the owner of the vehicle, place of registration, address, etc. in real image. It is observed in the experiment that the developed system successfully detects and recognizes the vehicle's plate in real images. Keywords: Number Plate Recognition; vehicle identification; optical character recognition; Character Recognition
Number plate acknowledgment is a type of programmed vehicle recognizable proof.  A number plate is the one of a kind recognizable proof of vehicle.  It is a picture preparing innovation used to distinguish vehicles by their own particular number plates. Constant number plate acknowledgment assumes an essential part in keeping up law requirement and keeping up movement rules. It has wide applications ranges, for example, toll court, stopping region, exceedingly security territories, visitor's regions and so forth. Number plate acknowledgment is intended to distinguish the number plate and afterward perceive the vehicle number plate from a moving vehicle consequently. Programmed number plate acknowledgment has three noteworthy parts: vehicle number plate extraction, character division and Optical Character Recognition (OCR).Number plate extraction is that phase where vehicle number plate is recognized. The recognized number plate is pre-prepared to evacuate the clamor and after that the outcome is passed to the division part to portion the exclusively characters from the removed number plate. The
The project was designed keeping in mind the automation of the number plate detection system for security reason that could replace the current system of manual entry. This project was a success in recording the number plate of a vehicle although it has got its own limitation of image processing and other hardware requirements. From this project we learn about image processing and OCR (Optical Character Reader), hardware interface in this paper, the automatic vehicle identification system using vehicle license plate is presented. The system use series of image processing techniques for identifying the vehicle from the database stored in the PC. The system is implemented in Matlab and it performance is tested on real images. The simulation results shows that the system robustly detect and recognize the vehicle using license plate against different lightening conditions and can be implemented on the entrance of a highly restricted areas.
positions, identification, course and speed, which network is shown in Figure 1. It mainly aims at avoiding collisions between ships. The link budgets allow receiving transmitted AIS signals from space, and consequently a global maritime surveillance can be considered. However, some challenges arise, especially message collisions due to the use of a Self Organized Time Division Multiple Access (SOTDMA) protocol (not designed for satellite detecting). Thus, advanced signal processing for separation of received signals is needed.
Besides being a proof-of-concept sensor for paper grade identification, this sensor’s inherent flexibility allows the same set-up to be used both for experimentation purposes and as an industrial standard sensor when the monochromator is removed. A series of experiments were conducted to study the effects of various chemicals in the paper and other factors that might influence the fluorescence due to lignin from the samples. Fluorescence intensity is a relative measurement that depends on instrument characteristics. Instrument factors, such as light source fluctuations, optical misalignments, and drift in the detector electronics, also affect fluorescence intensity measurements. Intensity measurements are also affected by nonspecific background fluorescence. Photobleaching of the fluorophore is another potential source of error in intensity-based fluorescence. Additionally, the presence of optically absorbing compounds in the sample can introduce additional measurement artifacts. This makes comparison of data taken with different instruments, or even with the same instrument at different times, difficult. Fluorescence intensities can be standardized only in conditions close to ideal and hence this attempt is not to standardize the fluorescence intensity values for each grade, instead, it is to provide a sensor that would distinguish between grades. In distinguishing between grades, it can be conveniently assumed that all grades are subjected to the same external conditions and also the output from every sample is subjected to the same instrument factors. All fluorescence intensity graphs obtained from this research have therefore been normalized to the peak values since it is the trends in the graphs and the ability of the sensor to distinguish between grades that matter. The sensor could be made more accurate by using ratiometric measurements, however, ratiometric measurements require an increase in instrument complexity and it is also instrument-dependent.
F. Pasqualetti, F. D¨ orfler, and F. Bullo. “Attack Detection and Identification in Cyber-Physical Systems - Part II: Centralized and Distributed Monitor Design,” in IEEE Transactions on Automatic Control, Feb. 2012, Submitted. F. Pasqualetti, A. Bicchi, and F. Bullo. Consensus computation in unreliable networks: A system theoretic approach. IEEE Transactions on Automatic Control, , 57(1):90-104, 2012.
The study attempted to design and develop a Cashless Pay- ment System with an AutomaticIdentification and Data Collec- tion (AIDC) technology such as Barcode. The study tried to provide a solution to the existing process of conducting cash- based payment transaction in an educational institution. It fol- lowed the stages of the Incremental Model but was limited only to the following stages: Planning, Requirements Analysis, De- sign and Development, and Testing. The deployment stage was not covered since the researcher only focused on the de- sign and development of a prototype system.
This describes the design of RFID(Radio Frequency Identification) based security and access control system which can be useful for securing data in many fields to complete this task the combination of RFID and biometrics are used when this RFID is installed at the hotel entrance it detects and verifies for a match where the image of user is registered if it matches then the access is granted otherwise an alarm turns on and the suspect can be caught. Paper is organized as follows. Section II describes automatic text detection using morphological operations, connected component analysis and set of selection or rejection criteria. The flow diagram represents the step of the algorithm. After detection of text, how text region is filled using an In painting technique that is given in Section III. Section IV presents experimental results showing results of images tested. Finally, Section V presents conclusion.This describes the design of RFID(Radio Frequency Identification) based security and access control system which can be useful for securing data in many fields to complete this task the combination of RFID and biometrics are used when this RFID is installed at the hotel entrance it detects and verifies for a match where the image of user is registered if it matches then the access is granted otherwise an alarm turns on and the suspect can be caught. This describes the design of RFID(Radio Frequency Identification) based security and access control system which can be useful for securing data in many fields to complete this task the combination of RFID and biometrics are used when this RFID is installed at the hotel entrance it detects and verifies for a match where the image of user is registered if it matches then the access is granted otherwise an alarm turns on and the suspect can be caught.
Running red lights (RRL) currently become a hotspot social issue. Although it is commonly mentioned to detect and warn by using traffic monitoring, this idea has still remain in human recognition. Therefore, this paper designs a method to remedy it, which can detect the behavior of the pedestrians crossing the road automatically. From the sequential images taken by traffic monitoring, the use of optical flow estimating the track of motion objects whether cross the designated area enables automaticidentification, then we carry out frames subtraction to isolate and identify the pedestrians from the moving objects. Combine the advantage of both algorithms, a system is presented to recognize the RRL event. Ultimately, the experiment confirms and indicates that what we proposed works effectively in some way.
Muhammad tahir qadri, et.1 , proposed Automatic number plate recognition system for vehicle identification using optical character recognition, ANPR is an image processing technology which uses number plate to identify the vehicle. The objective is to design an efficient automatic authorized vehicle identification system first detects the vehicle and captures the vehicle image. Vehicles number plate region is extracted using the image segmentation in an image. Optical character recognition technique is used for the character recognition. The resulting data is then used to compare with the records on a database so as to come up with the specific information like the vehicles owner, place of registration, address etc.,
We can notice that the use of the template matching technique is well suited for our system of automatic number recognition of soccer players. On one hand, template matching is particularly fast when used in context of our system, be- cause it requires only the recognition of numerical characters, rather than a wider range of alphanumerical characters as in other applications, such as license plate recognition (LPR). Indeed, our template stores in total only 10 images of one- digit numbers (0 to 9). Hence, the matching is performed against a maximum of ten stored images, in order to recognize the extracted character, which is compu- tationally very efficient. Moreover, the scale sensitivity of the template matching technique is used in our work as an advantage, since smaller dimensions of the template dimensions lead to a faster matching. On the other hand, the recogni- tion rate obtained by our implementation of this method in our system is much higher than those presented in the literature as discussed in Section 3.
In this work, automatic recognition of Arabic dialects is proposed. An acoustic survey of the proportion of vocalic intervals and the standard deviation of consonantal intervals in nine dialects (Tunisia, Morocco, Algeria, Egypt, Syria, Lebanon, Yemen, Golf’s Countries and Iraq) is performed using the platform Alize and Gaussian Mixture Models (GMM). The results show the complexity of the automaticidentification of Arabic dialects since. No clear border can be found between the dialects, but a gradual transition between them. They can even vary slightly from one city to another. The existence of this gradual change is easy to understand: it corresponds to a human and social reality, to the contact, friendships forged and affinity in the environment more or less immediate of the individual. This document also raises questions about the classes or macro classes of Arabic dialects noticed from the confusion matrix and the design of the hierarchical tree obtained.
necessitates the use of automated systems to maintain vehicle information. The information is highly required for both management of traffic as well as reduction of crime. Number plate recognition is an effective way for automatic vehicle identification. Vehicle Number Plate Detection (VNPD) is a mass surveillance system that captures the image of vehicles and recognizes their license number. Vehicle Number Plate Detection (VNPD) system is a type of intelligent transportation system (ITS).Some of the existing algorithms based on the principle of learning takes a lot of time and expertise before delivering satisfactory results but even then lacks in accuracy. In the proposed system an efficient method for recognition for Indian vehicle number plates has been devised. The algorithm aims at addressing the problems of scaling and recognition of position of characters with a good accuracy. The objective is to design an efficient automatic authorized vehicle identification system by using the Indian vehicle number plate such that the number plate of vehicle can be identified accurately and to implement it for various applications such as automatic toll tax collection, parking system, Border crossings, Traffic control, stolen cars etc In this proposed system , different phases such as number plate localization, character segmentation & recognition of the number plates are carried out. The system is mainly applicable for non standard Indian number plates by recognizing single & double line number plates under different varying illumination condition and works on multilingual, multi colour number plates according to Indian condition.
After model selection via cross validation, our to- tal feature space dimensionality varies between 2914 for the precedent only feature set and 16615 for the question + subsequent feature set. Distinct n-gram and POS n-gram features are considered for each of same speaker and different speaker for precedents and subsequents so as to capture the distinction between the two. Examining the rel- ative number of features selected for these sub- feature sets also gives a rough idea of the strength of the various cues. For instance, same speaker feature dimensionality tended to be much lower than different speaker feature dimensionality, sug- gesting that considering context uttered by the re- spondent is a better cue as to whether the question is rhetorical. Additionally, unigrams and bigrams tend to be more useful features than POS n-grams for the task of rhetorical question identification, or at least considering the less common POS n-grams is not as predictive.
NVIS Compatibility. To obtain the possibility to use both display unit and NVG (Night Vision Goggle) at the same time (night driving), a specific technical solution is selected. By using special optical filters on NVG and display unit, the haring of optical spectra is achieved. NVG are filtered using appropriate filters, and a display unit is filtered to eliminate excess of NIR radiation, so the display can be operated successfully using the naked eye, and without disturbing NVG . A display used in NVIS compatible mode has limited gamut (“poor” reproduction of red).
Over the ongoing years, Moving object detection is an imperative and vital part in the field of computer vision because of its extensive variety of utilizations like video observation, checking of security at air terminal, law requirement, video compression, programmed target identification, marine surveillance and human action recognition. Surveillance frameworks have increased incredible significance because of expanding security demands. Investigating the whole place is a critical and troublesome undertaking. In this manner surveillance systems are generally utilized in numerous regions. Generally, moving item is identified by two kinds of Camera: Static camera and Moving camera. Static camera recognizes the object by the Background subtraction Algorithm and screens the similar area. However, the supposition of the stationary camera has limits of the use of detection algorithm on account of increment of moving camera stages, for example, vehicles, robots and cell phones. Moving camera can screen bigger regions in its moving way. The video frames of a stationary camera will have a similar background, however it can't be the equivalent for moving camera frame since every one of the purposes of the video frames will change their position on each move. A video is a gathering of fundamental structural units, for example, scene, shot and frame related with sound information.
While automatic processing of DA is relatively re- cent compared to MSA, it has attracted a consid- erable amount of research in NLP (Shoufan and Al-Ameri, 2015). Most of it focuses on (i) collect- ing datasets from various sources and at different levels (Zaidan and Callison-Burch, 2011; Khalifa et al., 2016; Abdul-Mageed et al., 2018; Bouamor et al., 2018), (ii) creating processing tools (Habash et al., 2013; Al-Shargi and Rambow, 2015; Obeid et al., 2018) (iii) developing DA to English ma-
2.2 Acquiring the Automatic Thesaurus There are many alternative distributional similarity measures proposed in the literature, for this work we used the measure and thesaurus construction method described by Lin (1998). For input we used grammatical relation data extracted using an automatic parser (Briscoe and Carroll, 2002). For each noun we considered the co-occurring verbs in the direct object and subject relation, the modifying nouns in noun-noun relations and the modifying ad- jectives in adjective-noun relations. We could easily extend the set of relations in the future. A noun, ,