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The article describes the concept and design of indoor distributed localization system. Presented solution was designed primarily for swarm system and was aimed to cooperate with other environment recognition system used for mobile robots. Usage of network connected set of processes, running across simple Linux based computerized platform, provides high redundancy and platform interoperability.

In this paper, the recognition system of fuzzy clustering based on BP feature screening was put out. The figure specimens of experiment were filtered through BP network, and the result of screening was fit into the clustering source. At last fuzzy clustering was carried out by constituting the fuzzy relation matrix. The result of experiment demonstrates that this method has very high noise immunity capacity and overcame the limitation of traditional algorithm with single factor recognition. The recognition rate and precision ratio were greatly improved at the same time.

The vehicle license plate recognition system is the intelligent traffic management system based on the image and the character recognition technology, which is an important part of the intelligent transportation system. This paper introduces a method of vehicle license plate location based on edge detection and morphological operations, virtual instrument is combined with machine vision of the license plate recognition method [1]. Finally the license plate number of the vehicle is get. Experiment results show that such method can simplify the algorithm and has some correct location rate.

PCB defect detection based on AOI is the key technology to realize the automation production of PCB, and the mechanical structure design of the recognition system is one of the most important technologies in the detection system, too. By modeling the main hardware of mechanical structure of the system, we have integrated the whole hardware structure of the detection system. In this paper, we firstly design the general structure of the PCB recognition system. Then, we propose five axis positioning platform and PCB installation device. Finally, the designs of PCB belt conveyor and image acquisition device are completed. By using the integrated hardware structure combined with software control, we can realize intelligent recognition for PCB detection.

With the rapid development of transportation, more application of computer, communication and intelligent detection technology appeared in transportation field. The license plate recognition system based on template matching is researched in this paper. The preprocessing to the image such as binarization, tilt compensation and edge extraction has been finished, and then the positioning and segmentation of image are realized. After the normalization to the image, the license plate recognition result based on template matching method is obtained through experiments.

This Paper proposes a quick matching method for vehicle plate data based on NoSQL database technology considering the huge amounts of traffic information, the method uses the basic traffic network information database which built based on vehicle license plate auto recognition system and it improves the effectiveness and applicability of huge data-matching. Besides, the paper fits the travel time by the time priority principle, and estimates the average travel time by the mean estimation and median estimation according to sample capacity. The practical application shows that this method can effectively improve the efficiency of the mass data processing, and obtain travel time information quickly.

In order to improve the accuracy of recognition system for fatigue facial expression of driver, driver fatigue expression of this paper, the detection method for key feature points in the fatigue facial expression image of driver is applied in the paper to establish a fatigue expression image recognition model based on attention mechanism. Experimental results show that the algorithm can improve the recognition rate of driver's expression image, so as to record fatigue expression image of driver more accurate.

With the development of science and technology, optical images with very high resolution have been able to provide a large amount of information. Therein the road target is the most widely used in optical image. Road target detection and recognition is extremely important for reducing a lot of practical work and greatly improving the efficiency of the target extraction and identification. Aimed at this problem, we propose a road target recognition method based on optical image.The method is realized by joining human recognize and identify, combining with the intelligence of computer processing and powerful place. So in this work, the method based on edge detection and Hough transform algorithm is exploded. The man-machine interactive recognition system (Road Target Extraction and Recognition System) is developed. The system is realized under Windows operating system. The tool is Visual C++ 6.0 software. The platform is MFC functions. The system is written in C++ language. The characteristics of the system are the strong pertinence and the simple operation. When the system is applied safely, the results are definite and clear.

Due to the quality of all aspects of the human body differ greatly, collecting attitude parameters,electronic scales can not achieve the precision requirements. Therefore, how to ensure a large range torque measurement accuracy becomes the core of a recognition system of dimensional distribution of body weight. In this paper, based on the original measure will convert measuring force to measure the distance , redesigning the said bed to improve test accuracy.

Aiming at the deficiency of large volume and complex installation monitoring system the traditional character recognition system, this paper proposes a character recognition scheme of Android intelligent terminal based on. This paper introduces the whole structure of the system, through the analysis and Research on the character recognition process, introduces the overall design process and recognition system, character recognition system client.

A set of paper defect extraction IP core based on FPGA is introduced in this paper. Relying on FPGA powerful data processing capabilities and parallel architecture, the paper image acquisition, pre-processing and defect extraction function were achieved in an IP core. The IP core has been testing and running in some paper defect detection and recognition systems. As a result the system was stable and reliable which could ensure to achieve a paper defect extraction function. And it contributes to the design of paper defect detection and recognition system.

Extraction of License plate region is an important stage in the intelligent vehicle license plate recognition system. A practical license plate extraction algorithm based on edge detection and mathematical morphology is presented, the algorithm mainly consists of six modules: pre-processing, edge detection, binaryzation and denoising, morphology operation, filtration of connected regions, finding license plate region. From the experiments, the algorithm can detect the region of license plate quickly with 98% average accuracy of locating vehicle license plate region.

Lithium battery film on-line defect recognition system is realized based on industrial charge-coupled device (CCD) to improve quality. Otsu algorithm is adopted for threshold instead of traditional method. Area of defect is sorted to get the largest defect and geometry and projective is extracted from image. Film defects of lithium battery recognition is realized based on Brightness Judgment and One-against-all support vector machine (OAA-SVM). Experiment results show that these methods are effective and feasible, the accuracy can reach 90%.

In order to get better image Semantics recognition, in this paper, a scene Semantics recognition system based on fuzzy reasoning is presented. The system contains three parts: image preprocessing, target recognition, and fuzzy reasoning machine. Compared with other methods, the outputs of pattern classifiers are fuzzed, the fuzzy relationships between targets are extracted, and fuzzy inference is performed using fuzzy automata. The experiment indicates that this method could overcome the problems of false positive and false negative of pattern classifiers, and perform relatively more accurate image semantics recognition than other existing methods.

In order to realize highly intelligent and automatic species identification and recognition, we obtained the images of 11 varieties and each variety includes 50 seeds. For each image, we acquired 33 characteristics including shape, color and texture characteristics. And then we constructed the Artificial Neural Network and Support Vector Machine model to train and identify different varieties. We built the recognition system based on Visual C++ 6.0 and OpenCV library.Results shows that the SVM method has higher recognition effect than neural network overall and the recognition effect is more stability, the overall self-_recognition performance can reach 100% and test accuracy can reach 85%. The recoginition System base on Visual C++ runs faster than that of Matlab, which is more suitable for real-time varieties identification.

An embedded vision recognition system is developed for a regular UAH to provide guidance information during hovering and landing. An innovative landing mark has been designed to facilitate the image processing while provide relative heading, height, and coordinate for navigation. The system can provide 30 Hz updating rate to the UAH avionic system. Simulation and real-world tests have shown promising performance and results for future applications.

Based on machine vision principle, automatic recognition system is advanced to distinguish hub classification with different types. Firstly, the dark room environment is set up to eliminate the environmental interference. Secondly, the height of automobile hub is obtained with the grating ruler, and the diameter of automobile hub is achieved through image contours analysis. Finally, hub classification is accomplished through the Hu moment analysis of hub holes. Experiments show that the system can meet the needs of recognition online for hub classification, which can improve productivity effectively, and is of great application value.

The tilt license plate correction is an important part of the license plate recognition system. Traditional correction methods are based on one theory. It is difficult to use the advantages of different approaches. We propose some methods to help improve the tile license plate correction: a bounding box selection method based on similar height and a mutual correction method based on fitted parallel straight lines. Moreover, we use wide bounding boxes to segment touched characters. If the method based on parallel lines fails, another method, such as PCA-based one, can be used for complement. Experimental results show the proposed method outperforms others.

Bar code technology has been widely used with the development of computer application, which studies information identification by bar code and conversion from bar code information to computer language for automatic input, identification and statistics. This paper presents system design and realization of recognition system for one-dimensional bar code according with ISBN encoding rule. Encoding rule of common bar code is introduced at first. Bar code image is preprocessed by binaryzation, then the image noise caused by print quality and dirt is filtered by a mean value method. The actual width of bars and intervals are measured to identify contained digital information in one-dimensional bar code image. The result show that the method presented has good accuracy, quick speed and strong robustness for realtime application.

In order to meet the need of real-time and dynamic monitoring of intelligent transportation, a License Plate Recognition (LPR) System Based on ARM S3C2440 is introduced and a vehicle license recognition system is designed and realized. This thesis comparatively explains the tasks and problems and dose analytic research across all phases of the system. Image binary and slant rectification also be discussed, which are difficulty points in LPR. According to the study of the license plate images, we use hough transformation and image reverse rotation , a inclined rectification method was proposed. The experimental results show that the approach is excellent in the accuracy with rapid speed and is in the robustness.

With the rapid development of urbanization, the urban system is becoming increasingly large and complex. Building a comprehensive, standardized and efficient urban road-oriented recognition system is the urgent work currently, which plays critical roles for improving the quality of urban living environment and supporting the urban transportation system. This article is mainly focused on describing the current status of urban road information indicating system and its basic requirements.

Aiming at improving the identification and judgment on objectives of unmanned weapon system in the battlefield, this paper puts forward a new efficient method to infuse conflict evidence orienting towards shortcomings existing in the Dempster-Shafter (D-S) evidence theory when fusing conflict evidence. This paper is to improve the D-S Evidence Theory, by firstly conducting research on the influence of a certain operational environment on the sensors precision in the unmanned weapon system, and by secondly establishing sensors weight values based on fixed basic probability assignment by exploiting AHP. The improved approach can enhance the reliability of identification result, which has been proved via simulation experiments, and it improves the performance of target recognition system to a certain extent.

Surface electromyography (sEMG) signals, a non-invasive bioelectric signal, can be used for the rehabilitation and control of artificial extremities. But this signal is so weak that the electrical voltages ranging from -5 to +5 mv. In order to eliminate the 50Hz noise included in sEMG and hold details of the signal, IIR50HZ notch filter and FIR 50Hz notch filter are design. The compared simulation results show that the application of FIR 50Hz is better than IIR 50Hz in sEMG patter recognition system.

This paper introduces a novel implementation of in-vehicle traffic signs and traffic lights recognition system based on FPGA multi-core processers. Images could be processed with multi-core parallel processor using the corresponding relationships of traffic signs’ color and shape. We implement this vehicle vision system on SOPC hardware platform.

RFID, a radio frequency identification technology, it is a kind of communication technology, through the radio signal to identify specific targets and to read and write data, without the need for recognition system with specific target is established between the mechanical or optical contact. Dangerous chemicals as a special commodity, has greatly improved the life of people, but its inherent danger to human survival threat. Based on RFID technology, this paper proposed some ways and methods of dangerous chemicals management, to strengthen the management of dangerous chemicals and reduce the heavy accident to occur with the people's lives and property loss.

In this paper, an image processing and recognition system of the coal and gangue has been studied. We adopt digital video processing technology of high performance---DaVinci technology to design the system, which is made up by the chip DM6437 and some peripheral auxiliary equipment. The system takes advantage of the high performance of the chip to process the real-time image collected by the CCD camera. The system uses optimized image processing and recognition algorithms, and makes the recognition of coal and gangue by the different characteristic of their histograms. In the system, the histogram and processing image of coal and gangue can be displayed on the monitor.

A new algorithm of vehicle license plate automatic recognition for exit and entrance was proposed in this research. Firstly, using the gray information of vehicle license plate to locate plate roughly, and secondly using the color characteristics of the plate for accurate positioning in the rough location region, and then correcting the horizontal tilt of the plate by the method of Hough transform. After above processing, we adopt template matching method to recognize the plate characters. Experimental results indicated that the developed method can adapt to a variety of complex backgrounds and achieve the correct recognition of the vehicle license plate.

With the growth in number of vehicle, intelligent vehicle management has become the research hotspot, and license plate automatic recognition system is also of great concern as a important technology of intelligent traffic system. In this paper, Hough transform used to edge extraction, tilt correction algorithm and character recognition based on Haursdorff distance are discussed. At last, the license plate recognition system is designed and implemented, and then the experimental result is analyzed.

Feature extraction is a central processing in the automatic target recognition system, and noise filter is an important step in the feature extraction. A lot of research in noise filter has been proposed and used in image processing. In this paper, a noise filter algorithm based on area feature for vehicle recognition system is presented. Discussing the feature of vehicle for the recognition system, and the problem of the vehicle contour feature obtained from the traffic video. Analyzing the principle of the solve approach of the area-feature-based noise filter for vehicle recognition system. Implementing the program of the algorithm proposed in the following. Experiments have been conducted by many real vehicle images obtained from a real-time video produced by a monitor. The result shows that the new proposed method can remove the noise of the image signal for the vehicle recognition efficiently.