图像处理在足球机器人方面的应用

1、图像处理在足球机器人方面的应用.txt image processing applications in robot soccer on time to meet the right people is the life is happy; the time meets the wrong person is a heartache; the wrong time meet the right person is a ridiculous; the wrong time meets the wrong person is a sigh. Digital image processing ref

2、ers to the process of transforming the image signal into digital signal and processing it by computer. As an important sensory organ of intelligent robot, robot vision is mainly used for understanding and failure of 3D scene. It is an open topic in the study. Machine vision is mainly used in militar

3、y reconnaissance, dangerous environment of autonomous robots, postal, hospital and home service intelligent robot, assembly line workpiece recognition, positioning space robot automatic operation, etc.The following paper is about the application of image processing in soccer robot:Application of ima

4、ge processing in soccer robot systemMeng Mei (School of computer and information technology, Beijing Jiaotong University, Beijing 100044)Abstract: robot is a frontier subject in the field of comprehensive scientific research. Robot soccer competition is an effective way to achieve this scientific re

5、search. Among them, image processing is the primary research topic of soccer robot. In the robot soccer competition, to ensure the timely and rapid decision system provide effective information, the real-time requirements of image processing. This paper describes how to run BMP image encoding (RLE)

6、image compression format used in the data structure of soccer robot, and the experiment proves that the run length encoding suitable for soccer robot, can make the image processing efficiency of soccer robot system meet the unified coordinated work requirements.keyword image processing soccer robot

7、run length coding (RLE)1 IntroductionWith the rapid development of science and technology, the research and application of intelligent robot has become the focus of artificial intelligence research. Soccer robot is an international high-tech competition, in which robots can play football automatical

8、ly. To solve the cooperation of soccer robot in a variety of interference environment, must solve a series of problems in real time image processing, artificial intelligence, real-time dynamic cooperative control strategy, trajectory planning and wireless communication etc. There is no doubt that th

9、e eyes of intelligent robots are the important source of perception. Only when the correct information is obtained can the correct decision processing be carried out, and then the correct operation can be carried out. Therefore, image recognition is the first problem to be solved by intelligent robo

10、ts.2 principles of image processingDigital image processing (Digital Image Processing) is also called computer image processing. It refers to the process of transforming the image signal into digital signal and processing it by computer. Commonly used image processing research directions include ima

11、ge transformation, image coding compression, image enhancement and restoration, image segmentation and image recognition, image description, image classification (recognition) and so on. In the image processing of soccer robot, the main research fields are image segmentation and image coding compres

12、sion.2.1 image segmentationImage segmentation is to divide the image into some regions, in the same area, the image features are similar; and in different regions, the image features are far away. Image features can be the characteristics of the image itself, such as pixel gray, edge contour and tex

13、ture. The function of image is to extract useful information from images. In the process of image analysis, the image should be segmented first, then the segmented region is properly described, and then some analysis of the image can be done. It can be seen that image segmentation is an important pr

14、ocessing step before image analysis.Image segmentation is the basis of image processing. Although people have proposed many kinds of image segmentation methods, none of them can be applied to all images. How to choose the segmentation method is mainly based on the actual application environment and

15、specific target.Thresholding method is one of the most widely used segmentation techniques in image segmentation because of its simplicity, small computational complexity and stable performance.When the histogram of the image presents two or more blocks of different shapes, the threshold can be chos

16、en at the boundary of the two distribution. Therefore, the threshold method is mainly applicable to the target and background difference of the image region division.2.2 image coding compressionImage coding compression technology can reduce the amount of data (i.e. bits) to describe the image, so as

17、 to save the image transmission and processing time, and reduce the storage capacity. The compression can be obtained without distortion or under the condition of allowable distortion. Coding is the most important method in compression technology, and it is the earliest and more mature technology in

18、 image processing technology.Some images, especially computer generated graphics, tend to have many blocks of the same color. In these blocks, many continuous scanning lines have the same color, in this case it may not need to store color of each pixel, and only store one pixel value and the number

19、of pixels with the same color. This encoding is called run length coding, or run length coding, which is often represented by RLE (Run-Length Encoding). The run length encoding technique is quite intuitive and economical, and the computation is very simple, so the decompression speed is very fast. R

20、LE compression coding is especially suitable for computer generated graphics images, which is very effective for reducing storage capacity.The soccer robot system, is to obtain images through the camera or camera, and color graphics is also limited, according to the principle of run length encoding,

21、 application of RLE can effectively compress image data in the soccer robot system.Application requirements of 2.3 image processing in soccer robot systemIn the soccer robot system, the specific rules of the game: get in the camera pitch range, color is limited, green (site), orange (ball), blue or

22、yellow (team logo), pink or purple (to determine the position and direction). That is to say, in the image obtained by each acquisition card, as long as the location and direction of the six colors are clearly defined, the next step is to prepare the artificial intelligent collaboration module.Accor

23、ding to the actual game, the image processing system to achieve the goal is: the camera in the match, obtain the venue image at a certain interval, the acquisition card after the initial treatment, return the image on the playing field. This time, the image processing resulting in a table, any one c

24、olor. By querying the table, to be informed of the color in the image position.Therefore, according to the actual requirements of the system, it is effective and feasible to use the improved threshold segmentation method and run length coding compression for image processing.How to realize 3 image p

25、rocessing in soccer robot competitionThe vision system of soccer robot has higher requirements in real-time and anti-jamming. It needs fast and stable image processing method, and the realization of image processing is equal to the processing algorithm and the corresponding data structure. The data

26、structure of an image can be varied, not only to reduce the memory of the image as much as possible, but also can not make the image data lost, and can not affect the processing speed. This paper analyzes how to use the data structure which is obtained by threshold segmentation and run length coding

27、 in soccer robot, and how to process the image, and proves it by experiment.3.1 thresholding initial image segmentationDue to the light competition venues, the same color threshold image segmentation algorithm is not the same, therefore, before the game requires the field color sampling, to form the

28、 required to match the color threshold table. Methods: each color will play a set of representative numerical samples in the camera, through the graphical algorithm in pixel domain value formation and preservation of these 6 kinds of color is more precise threshold range, other colors are unknown co

29、lor. Get the threshold of all colors to get a three dimensional array:YUVClass 256COLORNUMBER3256 represents the range that the threshold can reachCOLORNUMBER is the total number of colors sampled (including unknown colors)3 record the Y, U, V information of each pixelThat is to say, through the YUV

30、Class table, can determine a pixel image obtained from camera, its color belongs to the acquisition of what kind of color so that the pixel image actually is divided into 6 colors.3.2 image pixel processingThe game is on the camera to obtain images of l*w in a certain time slice, processed by the co

31、mputer image acquisition card, the data is an array of bytes, each pixel value of RGB 3 units occupy a pixel array, namely l*w image acquisition card, the data conversion. The length of the byte array to store l*w*3 l*w pixel information. In order to facilitate the lookup of table YUVClass, it is ne

32、cessary to process the image array of RGB format into an array of YUV format. Its conversion formula is:Y=0.299*R+0.587G+0.144*BU= (-0.167) *R+ (-0.331) *G+0.500*B+127V= 0.500*R+ (-0.419) *G+ (-0.081) *B+127That is to say, each pixel of the Y/U/V values were YUVClass query table, if the three values

33、 in the table are determined, then the pixel is a collection of color, or as unknown color, this will be a length of image data conversion for the growth of l*w*3 m_colorimgl*w l*w is an array of bytes, so as to obtain a multi value image, each pixel in the image color values from 06.According to th

34、e actual system requirements, we do not need to store each pixel of the image, only need to obtain the location of the 6 colors. Therefore, the essence of run length coding is that the multi valued image is converted into a format of one-dimensional array stored by the data structure run, and the da

35、ta structure is as follows:Struct runPublic:Short x, y, width; / / run pixel position and width of the structure of Bank of ChinaCclass color; / / run structure of the color symbolInt parent, next; / / run in the list on the next node;The essence of this data structure is to form a run structure wit

36、h consecutive rows of pixels of the same color. In fact, in the robot soccer games, the venue of the color is mostly continuous, as the site of the green accounted for a large proportion, but the decision is the main needs of players, the other players and the ball and goal position. The amount of i

37、mage information required for this data structure is much less than that of the multi valued image storage method without reducing the amount of the primary valid information.The four connected operation of the run structure list is used to set the parent node of the run structure of the same color

38、in vertical and horizontal direction as the earliest one. In the image logic, the image is further divided into 6 color regions.3.3 image processing of effective informationRun structure is only the image pixel arrangement, he only records the color information of the collected pixels, if you want t

39、o judge the position of the football robot, but also need to combine with the relevant data. In order to facilitate further processing, the generated run structure is converted into region structure again:Struct regionInt color; / / color numberInt x1, Y1, X2, Y2; / / the horizontal and vertical coo

40、rdinates of the maximum and minimum valueFloat cen_x, cen_y; / / centroid horizontal and vertical coordinates of a region unit (the position)Int area; / / pixel areaInt run_start; / / the first run structure of the region structureInt iterator_id; / / ID onlyRegion *next; / / a region structure in t

41、he list;The most important data of the region structure is the center of mass of the transverse and longitudinal coordinates of the region unit,The center of mass meets certain conditions, such as the ball, the players, the opponent, the position of the goal and so on.Each color is a region structur

42、e, in the list at the same time, to form their own area from the list. Finally, all the 6 region structures of 6 colors are linked together to form the color_class_state table, and the head pointer of the list is given the data structure color_class_state of color information, which is as follows:Da

43、ta structure for storing color information in struct color_class_state/Region *list; / / pointer meter for each color of the region listInt num; / / region structure for each color numberInt min_area; / / minimum pixel area of the structure of a region numberRGB color; / / RGB value of each colorCha

44、r *name; / / color nameHere, the data obtained by the acquisition card, data processing is completed. Any position of the sampled color in the image can be quickly obtained from the color_class_state table. For example, the ball was orange, return its region list by the color name of the head pointer, then it can meet the conditions obtained by the centroid position of the ball, and then transmit the location information to the decision system, the robot can determine the next moment to the direction of motion an