A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control

Kiy, K. I.

doi:10.1007/978-3-319-11430-9_5

Cited by 4 publications

(20 citation statements)

References 5 publications

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“…A detailed description of the geometrized histograms method can be found in [10][11][12][13]. To construct the geometrized histogram for a color or grayscale image, this image is divided into strips St i , i = 1, …, n, of the same small width W with sides parallel to the horizontal (or vertical) axis Os of the image plane.…”

Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

“…Usually, there are too many intervals of the geometrized histogram of a grayscale or color image I kz to solve complex real problems. To reduce the number of them, a clustering procedure is introduced [10,12], which joins intervals Int kz that are close as intervals on Os and have close intensity (for the geometrized histogram of the grayscale image) and intensity-color characteristics (for the geometrized histogram of a color image). The joined intervals are called grayscale or color bunches.…”

Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

“…Here, the I component is equal to Y in (Y, C b , C r ). Using the methods developed in [10][11][12][13], we can attach to each color image the graph of color bunches STG (STructural Graph). Suppose that we deal with horizontal strips.…”

Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

“…Moreover, the technique will provide tools for distinguishing temporary and permanent road markings when they are both present on the road. Since any connected real object in the image generates a corresponding formal object in STG [10][11][12][13], we will investigate images of real road makings in this graph. For this purpose, the geometrized histogram of the color image and the geometrized histogram of its grayscale component will be employed.…”

Section: Problem Statement and Facilities For Its Solutionmentioning

confidence: 99%

“…It becomes especially clear when the road marking starts rather far from the bottom of the frame on its left or right boundary (this may occur in sharp turns). In this connection, it seems to be reasonable to apply the real-time geometrized histograms method for segmentation and description of color images [10][11][12][13] for finding and distinguishing road markings. This method makes it possible to find both white road marking of arbitrary shape and colored road making (for example, temporary one) and provides the technique for distinguishing them even under difficult illumination condition.…”

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confidence: 99%

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A new real-time method for finding temporary and permanent road marking and its applications

Dosaev¹,

Kiy²

2016

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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In this paper, a new real-time method for finding temporary and permanent road marking is proposed. The method is based on the geometrized histograms method for segmenting and describing color images. This method is able to deal with both rectilinear and curvilinear marking, as well as with color temporary and permanent road marking. It also makes it possible to distinguish temporary road marking from white permanent road marking. The developed method is stable under illumination and is able to work even for partially disappearing road marking, typical for late winter and early spring. In contrast to many other methods, this method does not require any information about camera parameters and calibration and is able to find road marking in images taken under unknown conditions. The proposed method has been implemented by a program written in C++, operating under Windows and Linux. The program operation has been tested on video records shot on typical Russian roads during different seasons and under diverse whether and illumination conditions. The processing speed is about 20 fps for a standard modern computer. Using parallel computing, this speed is reduced considerably. The results of program operation are presented and discussed. The developed program is a part of the computer vision component of the control system of the AvtoNiva pilotless vehicle. IntroductionThe problem of finding road markings is very important due to applications in advanced driver assistance systems (ADAS) and vision systems of autonomous vehicles. Efficient algorithms for finding road marking implemented in ADAS can prevent many road accidents and save many lives. The first efficient methods for real-time lane (road marking) detection were proposed and implemented by E.D. Dickmanns and his colleagues [1, 2]. These methods were dated back to the late 1980s and employed the so-called 4D approach proposed by E.D. Dickmanns [1]. Many methods based on Hough transform, RANSAC algorithm, and learning approaches, including deep learning of convolutional networks, have been proposed (see [3][4][5][6][7] and the references in these papers) since then. The most recent review of the results obtained in this area can be found in [6]. In spite of the serious progress in investigations on this topic, vital problems connected with lane marking, disappearing in early spring and late winter, wet places and occlusion still take place. It deserves special mentioning that temporary lane markings may have extremely high curvature, which may pose additional problems to the existing methods. Despite of the impressing results reached by application of convolutional networks, there are certain problems that arise in using them, such as overfitting, a large

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Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

Section: A Brief Description Of the Geometrized Histograms Methodsmentioning

confidence: 99%

Section: Problem Statement and Facilities For Its Solutionmentioning

confidence: 99%

mentioning

confidence: 99%

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A new real-time method for finding temporary and permanent road marking and its applications

Dosaev¹,

Kiy²

2016

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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Badminton motion capture with visual image detection of picking robotics

2020

International Journal of Advanced Robotic Systems

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In the process of strawberry easily broken fruit picking, in order to reduce the damage rate of the fruit, improves accuracy and efficiency of picking robot, field put forward a motion capture system based on international standard badminton edge feature detection and capture automation algorithm process of night picking robot badminton motion capture techniques training methods. The badminton motion capture system can analyze the game video in real time and obtain the accuracy rate of excellent badminton players and the technical characteristics of badminton motion capture through motion capture. The purpose of this article is to apply the high-precision motion capture vision control system to the design of the vision control system of the robot in the night picking process, so as to effectively improve the observation and recognition accuracy of the robot in the night picking process, so as to improve the degree of automation of the operation. This paper tests the reliability of the picking robot vision system. Taking the environment of picking at night as an example, image processing was performed on the edge features of the fruits picked by the picking robot. The results show that smooth and enhanced image processing can successfully extract edge features of fruit images. The accuracy of the target recognition rate and the positioning ability of the vision system of the picking robot were tested by the edge feature test. The results showed that the accuracy of the target recognition rate and the positioning ability of the motion edge of the vision system were far higher than 91%, satisfying the automation demand of the picking robot operation with high precision.

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Spatio-Temporal Slices for Frame Cut Detection in Video

Sorokina¹,

Fedoseev

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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The paper proposes an approach for unauthorized inter-frame video change detection using spatio-temporal slices. This approach can significantly reduce the amount of data processed and replace video processing with image processing that could be performed much faster. To test the efficiency of this approach, we consider a simple algorithm in analyzing adjacent rows of a slice and then classifying the rows based on its result. Experimental studies have revealed that this algorithm shows moderate results in terms of quality, but it has a great potential for improvement, which confirms the prospects of spatio-temporal slices for the given problem.

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A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control

Cited by 4 publications

References 5 publications

A new real-time method for finding temporary and permanent road marking and its applications

A new real-time method for finding temporary and permanent road marking and its applications

Badminton motion capture with visual image detection of picking robotics

Spatio-Temporal Slices for Frame Cut Detection in Video

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