Navigation Path Detection for Cotton Field Operator Robot Based on Horizontal Spline Segmentation

2017 ◽  
Vol 12 (3) ◽  
pp. 28-41 ◽  
Author(s):  
Dongchen Li ◽  
Shengyong Xu ◽  
Yuezhi Zheng ◽  
Changgui Qi ◽  
Pengjiao Yao
Keyword(s):  
Connected Domain ◽  
Least Squares Method ◽  
Visual Navigation ◽  
Morphological Processing ◽  
Binary Image ◽  
Cotton Field ◽  
Boundary Line ◽  
Cotton Wool ◽  
Navigation Path ◽  
Starting Point

Visual navigation is one of the fundamental techniques of intelligent cotton-picking robot. Cotton field composition is complex and the presence of occlusion and illumination makes it hard to accurately identify furrows so as to extract the navigation line. In this paper, a new field navigation path extraction method based on horizontal spline segmentation is presented. Firstly, the color image in RGB color space is pre-processed by the OTSU threshold algorithm to segment the binary image of the furrow. The cotton field image components are divided into four categories: furrow (ingredients include land, wilted leaves, etc.), cotton fiber, other organs of cotton and the outside area or obstructions. By using the significant differences in hue and value of the HSV model, the authors segment the threshold by two steps. Firstly, they segment cotton wool in the S channel, and then segment the furrow in the V channel in the area outside the cotton wool area. In addition, morphological processing is needed to filter out small noise area. Secondly, the horizontal spline is used to segment the binary image. The authors detect the connected domains in the horizontal splines, and merger the isolate small areas caused by the cotton wool or light spots in the nearby big connected domains so as to get connected domain of the furrow. Thirdly, they make the center of the bottom of the image as the starting point, and successively select the candidate point from the midpoint of the connected domain, according to the principle that the distance between adjacent navigation line candidate is smaller. Finally, the authors count the number of the connected domains and calculate the change of parameters of boundary line of the connected domain to make sure whether the robot reaches the outside of the field or encounters obstacles. If there is no anomaly, the navigation path is fitted by the navigation points using the least squares method. Experiments prove that this method is accurate and effective, which is suitable for visual navigation in the complex environment of a cotton field in different phases.

Navigation Path Detection for Cotton Field Operator Robot Based on Horizontal Spline Segmentation

2020 ◽  
pp. 1326-1340
Author(s):  
Dongchen Li ◽  
Shengyong Xu ◽  
Yuezhi Zheng ◽  
Changgui Qi ◽  
Pengjiao Yao
Keyword(s):  
Connected Domain ◽  
Field Operator ◽  
Visual Navigation ◽  
Morphological Processing ◽  
Binary Image ◽  
Cotton Field ◽  
Boundary Line ◽  
Cotton Wool ◽  
Small Areas ◽  
Navigation Path

Visual navigation is one of the fundamental techniques of intelligent cotton-picking robot. Cotton field composition is complex and the presence of occlusion and illumination makes it hard to accurately identify furrows so as to extract the navigation line. In this paper, a new field navigation path extraction method based on horizontal spline segmentation is presented. Firstly, the color image in RGB color space is pre-processed by the OTSU threshold algorithm to segment the binary image of the furrow. The cotton field image components are divided into four categories: furrow (ingredients include land, wilted leaves, etc.), cotton fiber, other organs of cotton and the outside area or obstructions. By using the significant differences in hue and value of the HSV model, the authors segment the threshold by two steps. Firstly, they segment cotton wool in the S channel, and then segment the furrow in the V channel in the area outside the cotton wool area. In addition, morphological processing is needed to filter out small noise area. Secondly, the horizontal spline is used to segment the binary image. The authors detect the connected domains in the horizontal splines, and merger the isolate small areas caused by the cotton wool or light spots in the nearby big connected domains so as to get connected domain of the furrow. Thirdly, they make the center of the bottom of the image as the starting point, and successively select the candidate point from the midpoint of the connected domain, according to the principle that the distance between adjacent navigation line candidate is smaller. Finally, the authors count the number of the connected domains and calculate the change of parameters of boundary line of the connected domain to make sure whether the robot reaches the outside of the field or encounters obstacles. If there is no anomaly, the navigation path is fitted by the navigation points using the least squares method. Experiments prove that this method is accurate and effective, which is suitable for visual navigation in the complex environment of a cotton field in different phases.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

scholarly journals A Novel Traffic Tracking System Based on division of Video into Frames and Processing

2013 ◽  
pp. 255-259
Author(s):  
Prabhakar Telagarapu ◽  
B. Jagdishwar Rao ◽  
J. Venkata Suman ◽  
K. Chiranjeevi
Keyword(s):  
Tracking System ◽  
Relative Size ◽  
Morphological Processing ◽  
Binary Image ◽  
Video Frame ◽  
Gray Scale ◽  
Binary Images ◽  
Morphological Image Processing ◽  
Car Detection ◽  
Analysis Technique

The objective of this paper is to visualize and analyze video.Videos are sequence of image frames. In this work, algorithm will be developed to analyze a frame and the same will be applied to all frames in a video. It is expected see unwanted objects in video frame, which can be removed by converting colour frames into a gray scale and implement thresh holding algorithm on an image. Threshold can be set depending on the object to be detected. Gray scale image will be converted to binary during thresh holding process. To reduce noise, to improve the robustness of the system, and to reduce the error rate in detection and tracking process, morphological image processing method for binary images is used. Morphological processing will be applied on binary image to remove small unwanted objects that are presented in a frame. A developed blob analysis technique for extracted binary image facilitates pedestrian and car detection. Processing blob’s information of relative size and location leads to distinguishing between pedestrian and car. The threshold, morphological and blobs process is applied to all frames in a video and finally original video with tagged cars will be displayed.

Nuevos registros narrativos en el periodismo cómic. Un estudio de caso: La grieta

2021 ◽  
Author(s):  
Antonio López-Hidalgo ◽  
Isaac López-Redondo
Keyword(s):  
Identity Crisis ◽  
The Arctic ◽  
Boundary Line ◽  
Comic Strips ◽  
Non Fiction ◽  
Starting Point ◽  
Close Relationship ◽  
The Impact ◽  
Verbal Analysis ◽  
Number Of Authors

There is an old and close relationship between comic and journalism which is reflected in newspapers through caricatures, bullet points and comic strips. However, comic journalism has emerged in the last decades as a new genre, a creative formula that hybridize comic codes and routines with narratives resources used in inmersive journalism. In the early 1990s, Joe Sacco stood out among a number of authors who popularized this new format, became aware of the journalistic genre condition as an information medium and sought his own formula for telling non-fiction stories. The photographer, originally published in 2003, involved the inclusion of photographs to make this formula more realistic and to describe Didier Lefèvre´s experience in the war in Afghanistan in 1986. In 2016, journalists Carlos Spottorno and Guillermo Abril published The crack, a story that once again mixes journalism and comic codes, where photographs subjected to a special chromatic treatment replace the drawings in each vignette. This study analyzes the impact and evolution of comic journalism through this field diary of two reporters who travel the path from Africa to the Arctic follow a boundary line that extends from Africa to the Artic, in order to unravel the causes and consequences of Europe’s identity crisis. A work translated into several languages and awarded with international prizes, which opens up new paths for narrative and aesthetic experimentation in the field of comic journalism. This paper takes as a starting point the theoretical review of the contributions made around the study of the connections between comic and journalism and focuses on the iconic-verbal analysis of The crack, completing the work methodology with open-ended interviews with the authors of the mentioned work. Resumen La relación entre el cómic y el periodismo es antigua y estrecha, con su reflejo en los diarios a través de la caricatura, la viñeta y la tira cómica. Sin embargo, en las últimas décadas ha surgido un nuevo género: el periodismo cómic, una fórmula creativa que hibrida códigos y rutinas del cómic con recursos narrativos propios del periodismo de inmersión. A principios de los años noventa, Joe Sacco destacó entre una serie de autores que popularizaron este nuevo formato, tomó conciencia de la condición del cómic como género informativo y buscó una fórmula propia para contar historias de no ficción. El fotógrafo, publicado originalmente en 2003, supuso la inclusión de fotografías para dar mayor realismo a esta fórmula y narrar la experiencia vivida por Didier Lefèvre en la guerra de Afganistán en 1986. En 2016, los periodistas Carlos Spottorno y Guillermo Abril publican La grieta, un relato que vuelve a mezclar códigos procedentes del periodismo y del cómic, donde fotografías sometidas a un tratamiento cromático especial sustituyen a los dibujos en cada viñeta. El presente estudio analiza el impacto y la evolución del periodismo cómic a través de este diario de campo de dos reporteros que recorren una línea fronteriza que comienza en África y llega hasta el Ártico, con el fin de desentrañar las causas y consecuencias de la crisis de identidad de Europa. Una obra traducida a varios idiomas y merecedora de varios premios internacionales, que abre nuevas vías de experimentación narrativa y estética en el terreno del periodismo cómic. El presente trabajo toma como punto de partida la revisión teórica de las aportaciones realizadas en torno al estudio de las conexiones entre cómic y periodismo y se centra en el análisis icónico-verbal de La grieta, completando la metodología de trabajo con entrevistas abiertas a los autores de la citada obra.

INFORMATION ACQUISITION IN DESERT ANT NAVIGATION

2006 ◽  
Vol 03 (01) ◽  
pp. 33-43 ◽  
Author(s):  
JUN GAO ◽  
LEI WANG ◽  
MEI BO ◽  
ZHIGUO FAN
Keyword(s):  
Body Length ◽  
Information Acquisition ◽  
Path Integration ◽  
Research Work ◽  
Polarized Light ◽  
Visual Navigation ◽  
Desert Ant ◽  
Navigation Path ◽  
Straight Line ◽  
Ant Navigation

Desert ant (Cataglyphis) is famous for its ability in navigation. In deserts with very few visual and odor information, the ant can return to its den almost along a straight line after foraging away in a distance of much more than thousands of times longer than its body length. Several kinds of information must be acquired during its trip, and the most important two are: path integration and visual navigation. Path integration is achieved by using sky light compass based on polarized light and odometer, while visual navigation relies on landmark based memory and matching. In this paper, a survey of research work on desert ant navigation from the viewpoint of information acquisition and fusion is presented, as well as the application of these kinds of information to navigate robots, especially bionic robots cruising in strange environment.

A Method for Binary Image Component Parallel Labeling Algorithm Based on CUDA

2013 ◽  
Vol 811 ◽  
pp. 538-542
Author(s):  
Tian Hong Mu ◽  
Yun Yang
Keyword(s):  
Parallel Processing ◽  
Software Architecture ◽  
Programming Language ◽  
Connected Domain ◽  
Large Scale ◽  
Binary Image ◽  
Labeling Algorithm ◽  
Label Algorithm ◽  
Image Component ◽  
Component Parallel

More internal transistor of GPU is used as a data processing rather than process control. Compared with the existing multinuclear CPU, it has more processors and higher ability of the whole parallel processing, which is suitable for a large scale super calculation based on desktop platform. CUDA platform, put forward by NVIDIA Company, which is a new hardware and software architecture of realized the general calculation of GPU combined with the high parallel ability, and adopt CUDAC programming language to realize a parallel binary image connected domain label algorithm based on CUDA. The algorithm uses eight connection body labels, which has the high parallel ability, the less association between steps and the efficiency of the great promotion space.

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 Binary Image Analysis Technique for Preprocessing of Excessively dilated characters in Aged Kannada Document Images

2019 ◽  
Vol 8 (4) ◽  
pp. 6660-6669
Keyword(s):  
Image Analysis ◽  
Noise Removal ◽  
Document Image ◽  
Morphological Processing ◽  
Binary Image ◽  
Document Images ◽  
Image Analysis Technique ◽  
Analysis Technique ◽  
Degraded Document ◽  
Scanned Documents

In this paper, variety of document image enhancement techniques are applied for removal of background noise in the degraded document images. The noise removal techniques are applied on different forms of noise including nonuniform illuminations, complex stain marks, user annotations, show through effect and foxing effect. In this work, Binary Image Analysis (BIA) Technique is proposed for removal of aging degradation in ancient document images of Kannada literature. The method involves multiple phases comprising of contrast enhancement, Gaussian smoothing, binarization, morphological processing, object detection using connected component analysis and filtering followed by marginal noise removal of non-textual regions. The document samples employed for experimentation comprised of more than 175 aged and highly degraded scanned documents of old Kannada literature and poetry that are massively affected by noise and 25 images from DIBCO datasets collected across 2009 to 2017. The results of the experimentation are quite satisfactory and suitable enough for processing of document images in the subsequent stages of OCR..The experimentations are compared with some widely used approaches like Sauvola, Otsu, Gaussian. It is noticed that the proposed method outperforms other noise removal methods in terms of character retentions for extensively degraded and aged document images.

scholarly journals Solution of problem of returning to the starting point of autonomously flying UAV by visual navigation

Informatics ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 17-24
Author(s):  
R. S. Zhuk ◽  
B. A. Zalesky ◽  
Ph. S. Trotski
Keyword(s):  
Visual Odometry ◽  
Video Camera ◽  
Visual Navigation ◽  
Navigation Algorithm ◽  
Localization And Mapping ◽  
Starting Point ◽  
Navigation Algorithms ◽  
Aerial Vehicle ◽  
Navigation Signals ◽  
The Moment

An autonomous visual navigation algorithm is considered, designed for “home“ return of unmanned aerial vehicle (UAV) equipped with on-board video camera and on-board computer, out of GPS and GLONASS navigation signals. The proposed algorithm is similar to the well-known visual navigation algorithms such as V-SLAM (simultaneous localization and mapping) and visual odometry, however, it differs in separate implementation of mapping and localization processes. It calculates the geographical coordinates of the features on the frames taken by on-board video camera during the flight from the start point until the moment of GPS and GLONASS signals loss. After the loss of the signal the return mission is launched, which provides estimation of the position of UAV relatively the map created by previously found features. Proposed approach does not require such complex calculations as V-SLAM and does not accumulate errors over time, in contrast to visual odometry and traditional methods of inertial navigation. The algorithm was implemented and tested with use of DJI Phantom 3 Pro quadcopter.

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