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Soft morphological filtering using hypergraphs

IOP conference Series: Materials Science and Engineering 2021年第1期1085卷

作者： Nuja M Unnikrishnan Mini Tom v Bino Sebastian K v Thomas Research Scholar Mathematics Department Bharata Mata College Thrikkakara Kerala India Professor Basic Science and Humanities Department SCMS School of Engineering and Technology Karukutty Kerala India Assistant Professor Mathematics Department Mar Athanasius College Kothamangalam Kerala India Assosiate Professor Mathematics Department Nirmala College Muvattupuzha Kerala India

A new framework of soft mathematical morphology on hypergraph spaces is studied. Application in image processing for filtering objects defined in hypergraph spaces are illustrated using several soft morphological operators-openings, closings, granulometries and ASF acting (a) on the subset of vertex and hyperedge set of a hypergraph and (b) on the subhypergraphs of a hypergraph. Experimental results dealing with the extension of soft morphological operators to gray scale images are presented in this paper. The results obtained are promising and is a better substitute for the prevailing methods.

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Edge detection of foreign matter suspension image of high voltage transmission line based on improved Canny operator

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Journal of Physics: conference Series 2021年第1期2087卷

作者： Yongjian Lin Kanglin Liu Baorong Wei Yantai Wei Kaiyuan Long Wuzhou Bureau U.H.V. Power Transmission Company China Southern Power Grid Co. Ltd. Wuzhou GuangXi 543002 China

In the edge detection of foreign object hanging image of high voltage transmission line, it is easy to appear that multiple responses will appear at one image edge point, which affects the detection effect. Based on the improved Canny operator, an edge detection method for foreign matter suspension image of high voltage transmission line is designed. The collected image is preprocessed in three steps: gray processing, optical correction and noise reduction, so as to better reflect the characteristics of the original image and improve the image quality. The non-uniform distribution of potential energy of foreign body hanging image data field is used to locate the image area of foreign body hanging. The morphological filter can extract the local noise and make the image clearer. The Canny operator is improved to obtain the partial derivative of the distance measurement function and automatically update the threshold to eliminate the multi-level response. The test results show that the method in this paper is better than the image edge detection method based on Canny operator and Sobel operator in three indexes: positive detection rate, false detection rate and missed detection rate.

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Application of machine learning methods for traffic signs recognition

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IOP conference Series: Materials Science and Engineering 2018年第1期315卷

作者： D v Filatov K v Ignatev A v Deviatkin E v Serykh V. Ulyanov (Lenin) St Petersburg State Electrotechnical University 'LETI' 5 Professora Popova Ul. St Petersburg 197376 Russian Federation

This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks' learning process.

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Real-time traffic light control system based on image processing and object detection

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AIP conference Proceedings 2023年第1期2579卷

作者： Juana Miriam Lawrence Ahmad Anwar Zainuddin Krishnan Subramaniam S. v. P. K. Satya Rohilah Sahak Norhana Abdul Rahman D. John Rakshys Department of Computer Science and Engineering Manipal International University Nilai Negeri Sembilan Malaysia

Traffic congestion causes a plethora of problems, from wasted time and fuel to air pollution. Much of the cause of congestion is due to the inadequacies in conventional traffic light systems. Therefore, this project proposes a smart traffic light control system that is able to redirect traffic based on real-time behavior using image processing and object detection techniques for vehicle detection. A Raspberry Pi and Pi Camera act as a controller to control a set of red, yellow and green LEDs simulating traffic lights. The Python programming language and OpenCv library was used for image processing. Frames from the video feed are converted into HSv, noise reduced using a median filter and morphological operations, thresholded into binary and extracted for contours. Objects are identified from the contours and counted. The system then controls the traffic light LEDs based on the number of vehicles present on each lane, making the optimal decision to reduce congestion and allowing cars on the lanes with heavier congestion to pass. The system displayed an object detection accuracy of 96.5%, 94%, 91%, 81% and 86% and in simulated normal, bright, medium, low light and fog. Furthermore, the dynamic system showed a 53% queue time reduction compared to conventional fixed-time systems. Results show that the system performs well under various levels of illumination and is feasible for practical use with existing traffic light infrastructure.

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image based book cover recognition and retrieval

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IOP conference Series: Materials Science and Engineering 2017年第4期263卷

作者： Kalyani Sukhadan v vijayarajan A Krishnamoorthi D Geraldine Bessie Amali School of Computer Science and Engineering VIT University Vellore-632014 India

In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

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vision Based Self Adaptive Algorithm for 6 Axis ABB Industrial Welding Robot

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IOP conference Series: Materials Science and Engineering 2021年第1期1123卷

作者： R Parameshwaran A Tony Thomas v Madhu vishal Department of Mechatronics Engineering Kongu Engineering College Perundurai TamilNadu-638060 India

The ultimate aim of this work 'vision Based Self Adaptive Algorithm for 6 Axis ABB Industrial Welding Robot' is to develop a self-adaptive RAPID algorithm based on the captured image of the work piece. The image of the work piece is captured using NI Guppy pro F031C camera which has 300 DPI with 120 FPS resolution. The captured image is transferred to the LabvIEW software for developing the self-adaptive algorithm through RS232 serial communication protocol. The LabvIEW vision assistant module is used to develop an algorithm based on the geometry of the captured image. The various image processing operations like Thresholding, morphological operation (Thinning), and edge detection are carried out. The caliper tool is used to measure the distance between the coordinate points (welding distance). With the aid of visual Basic, the measured values are converted into coordinates. The coordinates are used to develop a RAPID program with the aid of ABB Robot Studio library functions. The virtual server is established between the ABB Robot Studio and IRC5 Controller with the use of MOD-BUS protocol with vISA. After receiving the data from the MOD-BUS, the IRC5 controller moves the ABB Industrial Robot End effectors along with the welding gun for the welding purpose. The work piece is located on the designed jigs and fixtures. The different types of welding with different design can be incorporated with the vision Assistant module for further development. To illustrate the developed algorithm, robot assisted MIG welding process is carried out. The welded work-pieces are tested for its strength quality and the results are verified. Optimal welding parameters for the good quality of weldment identified by using Taguchi method of optimization.

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Shape and Relief Evaluation Using the Light Field Camera

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IOP conference Series: Earth and Environmental Science 2018年第2期194卷

作者： v E Makhov I I Sytko Mozhaisky Military Space Academy Zhdanov Street 13 St. Petersburg Russia 197082 Saint Petersburg Mining University 21 Line St. Petersburg Russia 199106

The paper considers an optical system for controlling the shape and micro-relief of products using a single-camera optoelectronic light field recorder. Based on National Instruments computer technologies, image processing algorithms and basic surface measurements have been developed. To accurately determine macro- and micro-relief parameters the authors propose algorithms for morphological analysis of two images obtained from a multi-focus light field file at a given depth of field. It is shown that the method of capturing the light field makes it possible to obtain the accuracy of surface relief by the height of its profile compared to other methods, while significantly reducing control requirements.

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Digital image processing techniques applied to pressure analysis and morphological features extraction in footprints.

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Journal of Physics: conference Series 2016年第1期705卷

作者： F J Buchelly D Mayorca v Ballarín J Pastore Laboratorio de Procesamiento Digital de imágenes ICyTE (Instituto de Investigaciones Científicas y Tecnológicas en Electrónica) Facultad de Ingeniería Universidad Nacional de Mar del Plata Argentina Consejo Nacional de Investigaciones Científicas y Técnicas - CONICET Argentina Grupo de Óptica y Láser Departamento de Física Universidad del Cauca Colombia

This paper shows the correlation between foot morphology and pressure distribution on footplant by means of a morphological parameters analysis and pressure calculation. Footprint images were acquired using an optical pedobarograph and then processed for obtaining binary masks and intensity images in gray scale. morphological descriptors were obtained from the binary images and the Hernandez Corvo (HC) index was automatically calculated for determine the type of foot. Pressure distributions were obtained from gray scale images making a correspondence between light intensity in footprints and pressure. Pressure analysis was performed by finding the maximum pressure, the mean pressure and the ratio between them that determines the uniformity of the distribution. Finally, a high correlation was found between this ratio and the type of foot determined by HC index.

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Intelligent systems for monitoring and controlling chip formation when cutting difficult-to-machine materials

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IOP conference Series: Materials Science and Engineering 2019年第1期560卷

作者： v v Maksarov v E Makhov Saint-Petersburg Mining University 21 Line St. Petersburg 199106 Russia Mozhaisky Military Space Academy Zhdanov Street 13 St. Petersburg 197082 Russia

This research addresses topical issues of creating industrial monitoring systems for chips, which are formed when materials are cut, based on light field-based optical detectors. A proposed scheme uses a light field (LF) method to register formed chips with an optical detector. An algorithms and monitoring methods for key geometric parameters of chip shapes are developed based on the analysis of images obtained from LF cameras. They feature digital image capturing and morphological analysis. For practical implementation of developed algorithms, National Instruments software platform is used. This research shows that the result accuracy in determining geometric characteristics of chips using the proposed solutions makes it possible to run diagnostics for cutting and material processing equipment.

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Acceleration of calculations using block algorithms for the difference solution of the heat equation

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Journal of Physics: conference Series 2019年第5期1368卷

作者： D L Golovashkin L v Yablokova I D Reznik Image Processing Systems Institute of RAS - Branch of the FSRC 'Crystallography and Photonics' RAS Molodogvardejskaya street 151 Samara Russia 443001 Samara National Research University Moskovskoe Shosse 34 Samara Russia 443086

In this paper, we propose taking into account the architectural features of the processor at the stage of constructing the numerical method itself. This idea is illustrated by the example of the synthesis of a new difference scheme for the heat conduction equation, which has traditionally been the object of testing innovations in the theory of difference schemes. The architectural feature hierarchical structure of the computer memory chosen led to considerable communication costs even when a single hardware computational flow was used for organising the calculations. This feature is accounted for in computational linear algebra by using block algorithms, and in the theory of difference schemes, by using the technique of programming 'tiling'. However, for the two-layer difference schemes of block algorithms for solving grid equations, prior to the proposed work, it was not known because of the impossibility of organising block calculations by using the existing schemes. Here, we propose a new method of constructing two-layer difference schemes and a mixed scheme with a shift as an example of the application of this method. In the course of the experiments, a five-fold acceleration of calculations according to this scheme was demonstrated relative to the traditional explicit model, with the same computational complexity.

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