Method for the navigation line recognition of the ridge without crops via machine vision

Some agriculture machinery like the transplanter,needs to operate by following the crop-free ridges.In order to improve working efficiency and quality,some autonomous navigation systems were developed and applied to ridge-following machinery.At present,agricultural navigation systems are mainly the satellite navigation system and the machine vision system.The satellite navigation system is difficult to apply to the machinery that needs to work by following the ridge because it cannot distinguish the shape of the navigated ridge and guide the machinery working along the ridge.In this study,697 cloudy ridge images and 235 sunny ridge images were taken in the field,and these images were used as the dataset.Moreover,a machine vision navigation method based on the color of ridges was proposed.Firstly,the regions of interest(ROI)in the ridge image were extracted according to the reaction time and the forward speed of the machine.Then,a gray reconstruction method was used to enlarge the color difference between the ridge and the furrow.The optimal threshold for the gray image segmenting was calculated real-timely by using the threshold segmentation method.Then,based on the contour detection method,the ridge contour which was not surrounded by holes was extracted.Finally,the approximate quadrilateral method was proposed to recognize the ridge center line as the navigation line.The method proposed in this study was verified by four types of ridges with different colors and textures.The experimental results showed that the recognition success rates of the light ridge,the dark ridge,the film-covered ridge,and the sunny ridge were 100%,97.5%,100%,and 98.7%,respectively.The recognition success rate of the proposed method was at least 8%higher than that of the existing ridge-furrow recognition methods.The results indicate that this method can effectively realize navigation line recognition.This method can provide technical support for the autonomous navigation of agricultural machinery,such as transplanters,seeders,etc.,operating on the ridge without crops.

Boosting the Expense and Performance of Ann/Hmm Approch for on-line Handwriting Recognition

This paper focuses on a state sharing method for an artificial neural network (ANN) and hidden Markov model (HMM) hybrid on line handwriting recognition system. A modeling precision based distance measure is proposed to describe similarity between two ANNs, which are used as HMM state models. Limiting maximum system performance loss, a minimum quantification error aimed hierarchical clustering algorithm is designed to choose the most representative models. The system performance is improved by about 1.5% while saving 40% of the system expense. About 92% of the performance may also be maintained while reducing 70% of system parameters. The suggested method is quite useful for designing pen based interface for various handheld devices.

Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.