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Dive into the research topics where Longyuan Guo is active.

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Featured researches published by Longyuan Guo.


International Journal of Pattern Recognition and Artificial Intelligence | 2017

Sub-Pixel Level Defect Detection Based on Notch Filter and Image Registration

Longyuan Guo; ShiNan Li; Wenjing Hu; Jianhui Wu; Bing Tu; Wei He; Xianfeng Ou; Guoyun Zhang

General machine vision algorithms are difficult to detect LCD sub-pixel level defects. By studying the LCD screen images, we found that the pixels in the LCD screen are regularly arranged. The spectrum distribution of LCD images, which is obtained by the Fourier transform, is relatively consistent. According to this feature, a method of sub-pixel defect detection based on notch filter and image registration is proposed. First, we take a defect-free template image to establish registration template and notch-filtering template; then we take the defect images for image registration with registration template, and solve the offset problem. After the notch-filter template filtering the background texture, the defect is more obvious; Finally the defects are obtained by the threshold segmentation method. The experiment results show that the proposed method can detect sub-pixel defects accurately and quickly.


International Journal of Pattern Recognition and Artificial Intelligence | 2017

Temporal–Spatial Symmetric Distributed Multi-View Video Coding Scheme

Guoyun Zhang; Canqun Xiang; Xianfeng Ou; Hong Yue; Longyuan Guo; Jianhui Wu; Bing Tu; Wei He

To improve the rate stability and make a balance for different viewpoints in distributed multi-view video coding (DMVC) system, a novel symmetric DMVC (SDMVC) scheme is proposed in this paper. In the proposed scheme, every frame from all views adopts the same encoding mode and stable output rates are achieved, which are significant to improve the transmission efficiency in the channel. Both temporal and spatial correlations are exploited, in addition, a novel side information (SI) generation algorithm aiming at better exploring the correlations of proposed scheme has been proposed to obtain better performance. The simulation results show that the proposed SDMVC scheme gets a much more stable rate than the asymmetric scheme, only with neglectable bit-rate increasing. Meanwhile, the proposed SI generation algorithm significantly improves the coding performance.


Multimedia Tools and Applications | 2018

Study of multiple moving targets’ detection in fisheye video based on the moving blob model

Jianhui Wu; Feng Huang; Wenjing Hu; Wei He; Bing Tu; Longyuan Guo; Xianfeng Ou; Guoyun Zhang

This paper discussed some improved algorithms for multiple moving targets detection and tracking in fisheye video sequences which based on the moving blob model. The view field of fisheye lens achieved 183 degree which used in our system, so it has more effective in the no blind surveillance system. However, the fisheye image has a big distortion that makes it difficult to achieve an intelligent function. In this paper we try to establish a moving blob model to detect and track multiple moving targets in the fisheye video sequences, in order to achieve the automation and intelligent ability for no blind surveillance system. It is divided into three steps. Firstly, the distortion model of fisheye lens was established, we are discussing the character of the imaging principle of fisheye lens, and calculate the distortion coefficient which can be used in the moving blob model. Secondly, the principle of the moving blob model was analyzed in detail which based on the fisheye distortion model. It was included four main algorithms, which the first is the traditional algorithm of background extraction; and the background updating algorithm; the algorithm of the fisheye video sequence with the background subtracted in order to get the moving blobs; the algorithm of removing the shadow of blobs in RGB space. Thirdly, we determined that every extracted blob is a real moving target by calculating the pixels with a threshold, which can discard the faulty moving targets. Lastly, we designed the algorithm for tracking the moving targets based on the moving blobs selected through calculating the geometry center. The experiment indicated that every algorithm has a better processing efficiency of multiple moving targets in fisheye video sequences. Compared the traditional algorithm, the improved algorithm can be detected the moving target in a circular fisheye image effectively and stably.


international conference on electric information and control engineering | 2012

Study of Motion Detection Technology Based on DaVinci Platform

Shuai Yuan; Guoyun Zhang; Jianhui Wu; Longyuan Guo

A motion detection method is presented based on Davinci platform. This paper adopts color histogram algorithm to detect moving target, which is operated on TMS320DM6446. The results indicate that the method presented has good accuracy and quick speed for real time application.


international conference on computer science and service system | 2012

Research of Face Detection Based on Davinci Platform

Shuai Yuan; Guoyun Zhang; Jianhui Wu; Longyuan Guo

A face detection method is presented based on Davinci platform. This paper adopts Adaboost algorithm to identify face, which is operated on TI TMS320DM6467. The results indicate that the method has good accuracy and quick speed for real time application.


international conference on model transformation | 2011

Study of face detection technology based on Davinci platform

Shuai Yuan; Guoyun Zhang; Jianhui Wu; Longyuan Guo

A face detection method is presented based on Davinci platform. This paper adopts Adaboost algorithm to locate face, which is operated on TI TMS320DM6446. The results indicate that the method presented has good accuracy and quick speed for realtime application.


international conference on mechanic automation and control engineering | 2011

Study of FPGA technology applied for stepping motor subdivision drive

Shuai Yuan; Guoyun Zhang; Jianhui Wu; Longyuan Guo

Limited by the manufacture technics, the stepping motor has big step angles and low frequency vibration, and can only be applied to those situations with low demand. This paper designs a method to realize subdivision drive for the stepping motor based on FPGA chip. Firstly, PWM control waveform data table are stored in embedded memory module of FPGA. Secondly, multiple PWM control signals are produced by the digital comparator synchronously. Finally, we realize subdivision control for the step angles of stepping motor. Test result shows that the stepping motor subdivision drive technology can decrease the stepping angle of stepping motor, improve the stabilization and flexibility and has preferable practical value.


international conference on electrical and control engineering | 2011

Study of measurement technology for abrasion of the coupler based on digital image processing

Shuai Yuan; Guoyun Zhang; Jianhui Wu; Longyuan Guo

An automatically inspecting method is presented to check the abrasion of the coupler with non-contact measurement technology. This paper adopts the method of digital image processing to analyze the coupler illustration. The results indicate that the method presented has good accuracy for engineering measurement.


artificial intelligence and computational intelligence | 2010

Infrared Image Area Correlation Matching Method Based on Phase Congruency

Longyuan Guo; Guoyun Zhang; Jianhui Wu

Infrared images have higher noise and lower resolution than visible images. This makes correspondence based on area correlation more difficult to achieve better disparity image. After analyzing the phase congruency transformed image, the paper presents area correlation matching method. First, the images are transformed by phase congruency. Next, the transformed images are matched based on area correlation. The experiment result indicates that the noise of images is restrained and feature is more distinct after phase congruency. The proposed method is more robust to infrared image than area correlation stereo matching method with gray value.


IEEE Geoscience and Remote Sensing Letters | 2018

Hyperspectral Imagery Noisy Label Detection by Spectral Angle Local Outlier Factor

Bing Tu; Chengle Zhou; Wenlan Kuang; Longyuan Guo; Xianfeng Ou

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Guoyun Zhang

Hunan Institute of Science and Technology

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Jianhui Wu

Hunan Institute of Science and Technology

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Xianfeng Ou

Hunan Institute of Science and Technology

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Bing Tu

Hunan Institute of Science and Technology

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Shuai Yuan

Hunan Institute of Science and Technology

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Wenjing Hu

Hunan Institute of Science and Technology

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Wei He

Hunan Institute of Science and Technology

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Pengcheng Yan

Hunan Institute of Science and Technology

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Xin Peng

Hunan Institute of Science and Technology

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Chengle Zhou

Hunan Institute of Science and Technology

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