A NOVEL ROTATION-INVARIANT TEMPLATE MATCHING BASED ON HOG AND AMDF FOR INDUSTRIAL LASER CUTTING APPLICATIONS Osman Arslan 1 , Berkan Demirci 2 , Halis Altun 3 , N.Serdar Tunaboylu 4 1,2,3 Department of Compuıter Engineering, Mevlana University, Konya, TURKEY 4 Department of Electrical & Electronics Engineering, Mevlana University, Konya, TURKEY oarslan82@yandex.com 1 berkan-demirci@yandex.com 2 haltun@mevlana.edu.tr 3 nstunaboylu@mevlana.edu.tr 4 ABSTRACT A new real-time rotation-invariant template matching is proposed for industrial laser cutting applications. The technique is based on Histogram of Oriented Gradients (HOG) algorithm to remove rotational angle before the template matching process. It exploits the HOG and the Average Magnitude Difference Function (AMDF) features for rotation- invariance. Since HOG features are robust against illumination effects, the proposed algorithm is suitable for harsh industrial environments. The final aim of this study is to devise a method to detect the contour of an object, which will automatically be cut from a sheet of material. 1. INTRODUCTION The laser cutting have been recently found a widespread industrial applications. In literature, there are many related studies on laser cutting [1-9]. Despite its widespread usage, laser cutting with machine-vision ability is rarely encountered in literature. An ability to automatically detect the contour of the object for laser cutting process will be beneficial and indispensable in some applications. In a recent study, ([10] Rao and Liu, 2011) a laser cutting machine with such an ability has been devised. In this study we propose a new approach based on the Histogram of Oriented Gradients (HOG) and the Average Magnitude Difference Function (AMDF) to develop a rotation and illumination- invariant method to detect the contour of the object to be cut. The proposed method will be used to develop smart machinery for the footwear industry, which will utilize image processing and soft-computing techniques to identify the contour of a pattern to be cut. The HOG algorithm proposed by Shashua et all [11], Dalal and Triggers [12] and is widely used in object and pattern recognition due to its ability to exhibit superior performance in many applications under different conditions [13,14]. The technique exploits the geometric properties of the object. Detection of an object based on its geometric properties seems to be a fundamental sub-problem in many classification and recognition applications. There are plenty of works in the literature which uses geometric properties in many applications such as hand gesture recognition [15], traffic sign recognition [16-19], human recognition [16][20], and recognition of several objects [21]. The final aim of this study is to develop an image processing module to integrate into a laser cutting process in footwear industry. The proposed module is a template matching which is based on the HOG and the AMDF algorithm. The algorithm, first of all, works on a raw image obtained directly from the camera without any preprocessing. Secondly the HOG features are extracted applying horizontal and vertical sobel operator on the raw image. The features are then normalized to deal with scaling problem. The AMDF is utilized to detect the rotational angle of the objects present in the image and remove the angle for a successful template matching. In the last step the template matching is performed to properly detect the contour of the object. The paper is organized as follows. Section 2 and 3 explain and elaborate the techniques, namely HOG and AMDF. Section 4 introduces the proposed template matching. Section 5 gives the results obtained by the proposed method and section 6 presents the results and draw conclusion. 2. HOG FEATURES FOR ROTATION DETECTION Despite there are lot of methods proposed in literature to detect the contour of an object, we propose to utilize a template matching based on HOG features and AMDF. HOG features exploit the characteristics of pixel orientation (θ) and magnitude values. It is proposed by Shashua [11] and Dalal [12]. The steps of extracting HOG features from given image could be listed as: First of all, a horizontal and vertical edge operators are applied on the image I to extract horizontal edge Ix and vertical edge, Iy separately as shown in Equation 1 and 2. In this step, horizontal and vertical Sobel filters, which are well-known edge operators in computer vision, namely Sx and Sy, are used to obtain Ix and Iy. In the second step, the magnitude of pixel gradient, Gxy, are calculated as given in Equation 3. Also the corresponding angle of the gradient   is found by Equation 4. In the last step, a histogram Proceedings of the 9th International Symposium on Mechatronics and its Applications (ISMA13), Amman, Jordan, April 9-11, 2013 ISMA13-1 978-1-4673-5016-7/13/$31.00 ©2013 IEEE