# A Study on M2M-based AR Multiple Objects Loading Technology using PPHT

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2 straight line on the (a, b) coordinate plane. In case no zero pixels in the input image are all expressed as straight lines on the (a, b) coordinate plane image and the pixel values located where the lines pass through are accumulated, a line on the (x, y) coordinate plane is shown to have a local maximum value on the (a, b) coordinate plane. Since all loci of the lines expressed by each point are summed, the (a, b) coordinate plane is commonly called an accumulator plane [7]. However, the method of expressing a straight line with a slope and a y-intercept is not appropriate to express all straight lines on the (x, y) coordinate plane. This is because to express the common straight lines of which slopes range from - to + in the binary image is difficult. Therefore, in practical realization, it is expressed as a point, (ρ, θ) on the polar coordinate system by means of other method. A line expressed as (ρ, θ) on the polar coordinate system means a straight line perpendicular to a line passing through this point and the origin, which is expressed in the following numerical formula (1): ρ = xcosθ+ysinθ (1) A point (x0, y0) (a) on the image coordinate system becomes a point (b) where many straight lines expressed as (ρ, θ) on the polar coordinate system intersect and it can be expressed as a line (c) on the (ρ, θ) plane as follows; Fig. 1 Common Accumulator Plane expressed on the Polar Coordinate System In this paper, reflecting local maximum values on (ρ, θ) coordinate plane, the marker recognition method was expanded to include not only a simple straight line but other general shapes. 3 Multiple objects loading Technology 3.1 Maker detection using PPHT In this paper, 8 bit input image is processed into binary image, no zero pixels are handled all equally and an Nⅹ1 sized matrix is stored in the memory storage as a pointer of the space where the result of Hough transform is to be stored. The most important thing in case of detecting a marker using PPHT, is to set a critical value to estimate it as a straight line on the accumulator plane. This paper set the critical value to optimize this in experimental condition and derived the result image. The methods of implementing the edge tracing algorithm to achieve contour information of the marker s contour out of the result image derived, and extracting edge points from the contour information existing within the marker region are as followings; First, if all edge points inside or outside of the marker region appear, one point out of tag region s contour information is selected and an edge point locating farthest from the point is extracted by means of Pythagoras theorem as shown in Fig. 2(a). Next, an edge point lying ISSN: ISBN:

3 farthest from the extracted point is investigated as in Fig. 2(b), and then an edge point locating farthest from the obtained edge point is extracted again as in Fig. 2(c). As illustrated in Fig. 2(d), a point which maximizes the area of the square becomes the rest one point. Based on the four points extracted, the marker ROI (region of interest) in marker tag can be extracted as shown in Fig. 2(e). the direction of line. This method only considers some voluntarily selected edge pixels, not increasing values for all edge pixels on the accumulator plane. In case a value in a specific location appears to be higher than the critical value, no more of value increase is allowed, and the edge pixels displayed by this point into a straight line will be ignored in the further calculation. Besides, since this method can reduce the calculation time drastically, it is highly effective in real time marker detection. (2) Fig. 3 Marker Detection using PPHT The above figure shows the tag detected using PPHT, from the original image captured from Webcam. For easy distinction, the detected parts are marked in bold. 3.2 Video output of replicated marker This study suggests a template matching method that makes warping into the marker registered in a square form from edge points which are extracted within the image, and performs matching. First of all, when the four edge points outside the marker are designated as respectively, a point where the straight line passing through and, and the line through and intersect becomes the center of the marker. The formula to calculate the center of the marker using the equation of straight line is as below; Fig. 2 Edge Points and Detection of Tag ROI PPHT (Progressive Probabilistic Hough Transform)[8] which is to be finally used for marker detection can calculate the beginning and the end of each line as well as (3) (4) ISSN: ISBN:

5 References: [1] Azuma, Ronald T., "A Survey of Augmented Reality, Teleoperators and Virtual Environments Vol. 6, No. 4, 1997, pp [2] T.P. Caudell and D.W. Mizell, "Augmented reality:an application of heads-up display technology to manual manufacturing processes," IEEE Comput.Soc. Press, Vol. 2, 1992, pp [3] I. Sutherland, A Head-Mounted Three Dimensional Display, Proceedings of Fall Joint Computer Conference, 1968, pp [4] A.I. Comport, E. Marchand, and F. Chaumette, A real-time tracker for markerless augmented reality, International Symposium on Mixed and Augmented Reality, [5] S. K. Feiner, S. Maclntyre and D. Seligmann, "Knowledge-Based Augmented Reality," Communications of the ACM, Vol. 30, No. 7, 1993, pp [6] R.O.Duda and P.E.Hart, Pattern Recognition and Scene Analysis, New York: Wiley, [7] Fernandes, L.A.F. and Oliveira, M.M., "Real-time line detection through an improved Hough transform voting scheme," Pattern Recognition, Elsevier, Volume 41, Issue 1, 2008, pp [8] C. Galambos, J. Kittler, J. Matas, "Progressive Probabilistic Hough Transform for Line Detection," cvpr vol. 1, 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Volume 1, 1999, pp ISSN: ISBN:

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