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- 검색키워드
- 저자 : Zuoyong Li (검색결과 3 건)
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Modified Adaptive Gaussian Filter for Removal of Salt and Pepper Noise
( Zuoyong Li ),( Kezong Tang ),( Yong Cheng ),( Xiaobo Chen ),( Chongbo Zhou ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.8
Adaptive Gaussian filter (AGF) is a recently developed switching filter to remove salt and pepper noise. AGF first directly identifies pixels of gray levels 0 and 255 as noise pixels, and then only restored noise pixels using a Gaussian filter with adaptive variance based on the estimated noise density. AGF usually achieves better denoising effect in comparison with other filters. However, AGF still fails to obtain good denoising effect on images with noise-free pixels of gray levels 0 and 255, due to its severe false alarm in its noise detection stage. To alleviate this issue, a modified version of AGF is proposed in this paper. Specifically, the proposed filter first performs noise detection via an image block based noise density estimation and sequential noise density guided rectification on the noise detection result of AGF. Then, a modified Gaussian filter with adaptive variance and window size is used to restore the detected noise pixels. The proposed filter has been extensively evaluated on two representative grayscale images and the Berkeley image dataset BSDS300 with 300 images. Experimental results showed that the proposed filter achieved better denoising effect over the state-of-the-art filters, especially on images with noise-free pixels of gray levels 0 and 255.
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Flight and Hover Control System Design for a Mini-quadrotor Based on Multi-sensors
Zhongli Ma,Huixin Li,Yanming Gu,Zuoyong Li,Qianqian Li 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.2
Mini-quadrotor is difficult to control in the air due to its small size and light weight. This paper presentsthe flight and hover control system for a mini-quadrotor, including design and simulation of calculations and controllers. Firstly, the attitude and position of the mini-quadrotor are obtained by distributed multi-sensors. Since attitudecalculation of aircraft needs a number of combined rotations and vectors transformed by rotation, quaternionsare applied to express the attitude model. About error compensation of gyroscope and accelerometer, IMU_Updataalgorithm of Mahony filter are applied and improved to realize data fusion [1]. In order to realize accurate hoveringat certain position, UWB (UltraWideband) are applied to gain positional information of mini-quadrotor and correctthe antenna delay caused sensor error by base station positioning. The discrete Kalman filter of original data is usedto achieve the optimized estimation of the airborne position. Px4flow optical flow sensor is able to gets velocityinformation and avoid the noise problem, which is caused by differential of position data. Then, the mathematicalmodel of a mini-quadrotor’s flight and hover control system can be established. Herein, integral items are solved bythe integral separation and integral limiting to mitigate the serious overshoot and oscillation of the system caused bythe cascade PID. Finally, the simulation of the attitude controller and position controller are applied with the MATLABSimulink library. The simulation result shows that the designed attitude controller and position controller canenable the mini-quadrotor to fly smoothly, move in all directions and hover.
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Tongue Image Segmentation via Thresholding and Gray Projection
( Weixia Liu ),( Jinmei Hu ),( Zuoyong Li ),( Zuchang Zhang ),( Zhongli Ma ),( Daoqiang Zhang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.2
Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.
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