scholarly journals RESEARCH ON VISUAL NAVIGATION PATH DETECTION METHOD FOR DENSE PLUM GROVE

2021 ◽  
pp. 111-118
Author(s):  
XiaoDan Ren ◽  
Haichao Wang ◽  
Xin Shi
Keyword(s):  
Color Space ◽  
Region Of Interest ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Visual Navigation ◽  
Least Square ◽  
Detection Accuracy ◽  
Navigation Path ◽  
Field Management ◽  
Path Detection

Aiming at the field management of plum grove in Inner Mongolia of China, taking the dense planting plum groves in Bikeqi town of Hohhot City as the research object, this paper proposed a visual navigation path detection algorithm for plum grove. By processing the video image information of plum grove, comparing RGB and HSV color space model, HSV color model was selected to separate the plant and background in V channel. Homomorphic filtering was used to highlight the region of interest in the image, Otsu was selected to segment the image, the intersection of plum trunk and ground was extracted as feature points, and the least square method was used to fit the navigation path. Through the comparative analysis of detection rate under different detection conditions in one day, the verification test of route accuracy was carried out. The experimental results show that: for dense planting plum grove, the average path detection accuracy of the algorithm is 70% and 73.3% under the condition of front light and weak light, respectively. The detection accuracy and real-time meet the requirements of plum grove field management, and the navigation baseline can be generated more accurately, which provides a preliminary basis for the realization of mechanical vision navigation in plum grove field management.

scholarly journals ANALYSIS OF VISUAL NAVIGATION EXTRACTION ALGORITHM OF FARM ROBOT BASED ON DARK PRIMARY COLOUR

2020 ◽  
pp. 219-228
Author(s):  
Zhongkun Hou
Keyword(s):  
Precision Agriculture ◽  
Least Square Method ◽  
Visual Navigation ◽  
Least Square ◽  
Actual Situation ◽  
Extraction Technology ◽  
Navigation Path ◽  
New Development ◽  
Extraction Algorithm ◽  
Development Prospects

With the development of information technology, precision agriculture has also ushered in new development prospects. The use of farm robots to accurately identify the navigation path is of great significance for achieving accurate positioning of agriculture. In this study, when analysing the extraction algorithm of farm robot visual navigation based on dark primary colours, a method for pre-processing and edge detection of farmland images based on dark primary colours is proposed. At the same time, the least square method of linear fitting is used for the navigation path of agricultural robot, and then the fitting program is executed. On this basis, combined with the actual situation of outdoor farming and greenhouse cultivation of crops, the effectiveness of the robotic visual navigation extraction algorithm was verified. The research results show that for any form of farmland cultivation, image extraction technology based on dark primary colours can effectively distinguish between soil and crops, and the visual navigation path of farm robots fitted with least squares is basically linear, which is consistent with the commonly used crops for farm planting. The legal route is basically the same, and then the effectiveness of the extraction algorithm is verified. It is hoped that this study will provide a certain reference and reference for the analysis of the field navigation robot visual navigation extraction algorithm based on dark primary colours.

The Traffic Sign Detection Algorithm Based on Region of Interest Extraction and Double Filter

2019 ◽  
Vol 13 ◽  
Author(s):  
Dongxian Yu ◽  
Jiatao Kang ◽  
Zaihui Cao ◽  
Neha Jain
Keyword(s):  
Region Of Interest ◽  
Detection Algorithm ◽  
Light Filter ◽  
Support Vector ◽  
Detection Accuracy ◽  
Traffic Light ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Sign Detection ◽  
Traffic Sign Detection

In order to solve the current traffic sign detection technology due to the interference of various complex factors, it is difficult to effectively carry out the correct detection of traffic signs, and the robustness is weak, a traffic sign detection algorithm based on the region of interest extraction and double filter is designed.First, in order to reduce environmental interference, the input image is preprocessed to enhance the main color of each logo.Secondly, in order to improve the extraction ability Of Regions Of Interest, a Region Of Interest (ROI) detector based on Maximally Stable Extremal Regions (MSER) and Wave Equation (WE) was defined, and candidate Regions were selected through the ROI detector.Then, an effective HOG (Histogram of Oriented Gradient) descriptor is introduced as the detection feature of traffic signs, and SVM (Support Vector Machine) is used to classify them into traffic signs or background.Finally, the context-aware filter and the traffic light filter are used to further identify the false traffic signs and improve the detection accuracy.In the GTSDB database, three kinds of traffic signs, which are indicative, prohibited and dangerous, are tested, and the results show that the proposed algorithm has higher detection accuracy and robustness compared with the current traffic sign recognition technology.

Ultrasonic Detection Algorithm Research on the Damage Depth of Concrete after Fire

2011 ◽  
Vol 368-373 ◽  
pp. 2229-2234
Author(s):  
Jiang Tao Yu ◽  
Yuan Liu ◽  
Zhou Dao Lu ◽  
Peng Zhao
Keyword(s):  
Ultrasonic Method ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Measured Data ◽  
Structural Member ◽  
Least Square ◽  
Propagation Time ◽  
Practical Application ◽  
Ultrasonic Detection ◽  
Damage Depth

To measure the depth of fire-damaged concrete by ultrasonic method, it was traditionally assumed that the concrete of the fire-damaged structural member could be simply classified into damaged layer and undamaged layer. Based on it, the damage depth can be calculated with a series of single-sided ultrasonic measured data. This method is simple and convenient but less accurate in the practical application. To improve the algorithm, hyperbola curves are adopted to simulate the varying of damage with depth in this paper. And parabolic curves are adopted to simulate the traces of ultrasonic wave in different measured distances. Therefore, the minimum propagation time can be obtained under different damage conditions. Through comparing the calculating results and measured data in different measured distances, the most likely damaged trend can be determined with least square method. At the end of this paper, examples are demonstrated to prove this algorithm feasible and more accurate than the traditional one.

A New Method to Detect P-Wave Based on Quadratic Function

2011 ◽  
Vol 267 ◽  
pp. 462-467
Author(s):  
Nan Quan Zhou
Keyword(s):  
Quadratic Function ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
P Wave ◽  
Good Effect ◽  
Rate Variation ◽  
Optimal Interval ◽  
Wave Detection ◽  
Wide Range

The paper presents a P-wave detection algorithm based on fitting function in the optimal interval. In the algorithm we used quadratic function to fit the P wave by this means of least square method in every interval, which was shifted in local range. Then we found the optimal fitting interval of P wave by comparing the error of fitting. Finally, we obtained the characteristic points of P wave by using the fitting function to fit P wave in the optimal interval. The performance of the algorithm tested using the records of the MIT-BIH database was effective and accurate. The algorithm on the wide range of heart rate variation and small P wave of ECG P-wave detection has good effect. Also it has some capabilities of anti-interference, particularly the false dismissal probability is quite low.

Lane Detection Based on Improved Canny Detector and Least Square Fitting

2013 ◽  
Vol 765-767 ◽  
pp. 2383-2387 ◽  
Author(s):  
Guang Hua Chen ◽  
Wen Zhou ◽  
Feng Jiao Wang ◽  
Bin Jie Xiao ◽  
Sun Fang Dai
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Least Square ◽  
Edge Detector ◽  
Canny Edge Detector ◽  
Least Square Fitting ◽  
Video Images ◽  
Canny Edge ◽  
Single Pixel

The video images of road monitoring system contain noise, which blurs the difference between the lane and the background. The lane detection algorithm based on traditional Canny edge detector hardly detects the single-pixel lane accurately and it produces pseudo lane. The paper proposes an effective lane detection method based on improved Canny edge detector and least square fitting. The proposed method improves the dual-threshold selection of traditional Canny detector by using the histogram concavity analysis, which sets the optimal threshold automatically. The least square method is used to fit the feature points of detected edges to accurate and single-pixel wide lane. Experimental results show that the proposed method detects the lane of video images accurately in the noise environment.

Subpixel Edge Detection Algorithm of the Glass Bottle Based on Zernike Moments

2011 ◽  
Vol 80-81 ◽  
pp. 1345-1349
Author(s):  
Hao Yang ◽  
Lei Pei
Keyword(s):  
Edge Detection ◽  
Fast Algorithm ◽  
Least Square Method ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Zernike Moments ◽  
Least Square ◽  
Measuring System ◽  
Zernike Moment ◽  
Glass Bottle

The accuracy of edge detection determines the accuracy of actual dimension measurement，in order to improve the measuring accuracy, this paper proposes a fast algorithm of detecting the glass bottle dimension based on Zernike moments. Firstly, combines the traditional Zernike moment-based method with Otsu adaptive threshold algorithm and a new fast algorithm for edge detection is proposed. Then uses this fast algorithm to detect the edge of glass bottle with subpixel-level and uses the least square method to fit ellipses formed by the glass bottle mouth and bottom. Calibrated the system with standard gauge block and obtain the actual dimension at last. Experimental results show that the improved algorithm not only can make the edge detection reach the subpixel-level accuracy, but also can avoid the edge misidentification and inefficient causing by repeatedly manual adjustments to select the threshold value when detecting the edge. Making a rapid, accurate, non-contact measuring system becomes a reality.

A Skew Detection Algorithm for PDF417 Based on Feature Point

2011 ◽  
Vol 128-129 ◽  
pp. 495-499
Author(s):  
Jian Hua Li ◽  
Ping Li ◽  
Xiao Dan Li ◽  
Yi Wen Wang
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
Detection Methods ◽  
Automatic Identification ◽  
Feature Points ◽  
Skew Angle ◽  
Bar Code ◽  
Character Code ◽  
The Common

The automatic identification of 2D (two dimensional) bar code PDF417 is very sensitive to skew angle, but, the common skew angle detection methods have shortcomings such as weak performance in time complexity. In this paper, based on the properties of PDF417 character code and the extraction of feature points, we get skew angle of PDF417 bar code image using the least square method. Experiments show that this algorithm has virtue of less computation and high accuracy.

scholarly journals Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection

2019 ◽  
Vol 9 (16) ◽  
pp. 3338 ◽  
Author(s):  
Tae-Gu Kim ◽  
Sheikh Faisal Ahmad ◽  
Byoung-Ju Yun ◽  
Hyun Deok Kim
Keyword(s):  
Rotation Angle ◽  
Detection Method ◽  
Region Of Interest ◽  
Least Square Method ◽  
Thickness Measurement ◽  
Least Square ◽  
Step Detection ◽  
Cutting Machine ◽  
Otsu Method ◽  
Binarization Method

An algorithm for measurement of the cutting blade of the ultrasonic vibration cutting machine used in an automation machine is proposed in this paper. The proposed algorithm, which is based upon a multi-step detection method, is developed for the accurate measurement of the cutting blade by exactly determining its rotation angle, length, and thickness. Instead of the commonly used Otsu method, we propose a new curvature-based adaptive binarization method, which provides more accurate details about the dimensions of the cutting blade. A region of interest containing the cutting blade from the acquired image is first extracted in the multi-step detection method, which is further processed to remove the noise, which increases the measurement reliability. An important feature of the proposed process is the restoration of the cutting blade’s tip data, which used to be lost during the fine noise-filtering process. The rotation angle and length are measured using the minimum rotated rectangle while the line fitting based upon the least square method is applied to increase the reliability of the thickness measurement. Experimental results validate the superiority of the proposed method over the conventional Otsu method.

A CONSTRAINED LEAST SQUARE METHOD FOR ESTIMATING A SMOOTH, NONNEGATIVE FORWARD RATE SEQUENCE

2005 ◽  
Vol 08 (07) ◽  
pp. 989-998 ◽  
Author(s):  
HIROSHI KONNO ◽  
SUMITO ITO
Keyword(s):  
Optimization Problem ◽  
Market Price ◽  
Optimal Solution ◽  
Region Of Interest ◽  
Least Square Method ◽  
Least Square ◽  
Smoothness Condition ◽  
Forward Rate ◽  
Programming Algorithms ◽  
Fitting Error

We will develop an efficient method for estimating a smooth nonnegative forward rate sequence using the market price of riskless bonds. This method is an improvement of the classical Carleton–Cooper's method based on standard least square method, which often generates a non-smooth forward rate sequence and hence is not used in practice. The method to be proposed in this paper is intended to resolve this difficulty. We will impose a smoothness condition while maintaining the fitting error within an acceptable level. The resulting optimization problem is shown to be convex in the region of interest. Therefore, we can calculate a globally optimal solution very fast by standard nonlinear programming algorithms. We will demonstrate that this method generates a smooth forward rate sequence at the expense of a very small increase of fitting error.

Study on the Navigation of Patrol Robot of Transformer Substation Based on Color Vision and RFID

2011 ◽  
Vol 268-270 ◽  
pp. 1259-1264 ◽  
Author(s):  
Song Hai Fan ◽  
Dong Xue Xia
Keyword(s):  
Real Time ◽  
Color Vision ◽  
Radio Frequency Identification ◽  
Color Space ◽  
Least Square Method ◽  
Least Square ◽  
Image Process ◽  
Position Information ◽  
Time Performance ◽  
Transformer Substation

The robustness and real-time performance are of the greatest significance for the navigation of the patrol robot in the transformer substation. To meet this demand, a navigation and position approach is presented in this paper based on color vision and RFID(Radio Frequency Identification) technology. In the presented system, the position information is provided by RFID tags and navigation is completed by the extraction of guidelines. Based on the deep analysis of the advantages and shortcoming of different color space, a new approach integrating the good real-time performance of grayscale image process and rich information in color images process is presented to improve the robustness and real-time performance of navigation. Fast Hough transform is selected and combined with least square method to detect the navigation line. Experimental results show that the presented method can meet the real-time and robust demand of the navigation of patrol robot.

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