Abstract—This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates. Keywords—Camera calibration, Ice detection, ice load measurements, image processing. I. INTRODUCTION TRUCTURE icing is a phenomenon influencing marine and offshore activities during cold seasons in Arctic regions [1]-[3]. Monitoring ice conditions plays an important role to apply de-icing in proper situations. Models have been established to predict the amount of ice load on marine structures [3], [4]. Ice detection and ice load measurements are challenges in marine icing research and have been investigated for years [5]-[7]. Current methods for modeling and measuring ice loads are based on physical properties, which need expensive equipment to be measured, and human interference, which causes safety hazards. Developing algorithms to predict and remove ice accumulation is automatically an essential component to reduce hazards and cost [1]. Image processing techniques have been established for ice monitoring, and are used to calculate the ice thickness on power transmission lines. The ice thickness on transmission lines is calculated applying edge Azam Fazelpour and Vlastimil Masek re with the Department of Electrical Engineering, Memorial University of Newfoundland, St. John’s, NL, Canada (e-mail: a.fazelpour@mun.ca, masek@mun.ca). Saeed R. Dehghani and Yuri S. Muzychka are with the Department of Mechanical Engineering, Memorial University of Newfoundland, St. John’s, NL, Canada (e-mail: srdehghani@mun.ca, yurim@mun.ca ). detection and thresholding algorithms. Ice thicknesses are calculated by the subtraction of uniced and iced line thicknesses [8]. In another study, two cameras are employed to capture images of an iced power transmission lines. The matched corresponding points are found in the images establishing correlation methods. The edges of accumulated ice are detected using 3D coordinates obtained from two existing images [9]. The ice thickness of a cylindrical structure is measured employing a thermal camera. Thermal imaging is not affected by background color and light [10]. The combination of visual and thermal imaging is conducted to calculate the ice thickness on a structure and leads to detect the ice area more accurately than using a single type image [11]. Current image based methods can measure ice thickness on simple structures. Ice load measurements based on image processing for complicated structure can provide more advantages for ice monitoring. In this paper, a method for ice load measurement defining the information of a known structure is developed. Using the structure information and camera position, a scheme of the structure is drawn in the image frame. An experimental setup is performed to capture images and obtain real measured data. Applying the threshold method and a morphological algorithm, the ice area is extracted from captured images. The ice load of each component of the structure is calculated and the total ice load is then obtained by the summation of component ice loads. II. METHODOLOGY Intersection nodes of the structure and its bar elements are defined in a determined coordinate system. This coordinate system is named the world coordinate system. The world coordinate system is converted to the camera coordinate system using extrinsic parameters, including rotation matrix, R, and translation matrix, t. These two matrices show the camera position and angle with respect to the world coordinate system. To obtain the structure coordinate in the image plane, intrinsic parameters are calculated using camera calibration. Intrinsic parameters are defined as a matrix, K, including focal length, image coordinate system origin, and correction parameters. Equation (1) shows converting a point in the world coordinate system,  ௪௖ , to the image coordinate system, ݌ ௜௖ , using intrinsic and extrinsic parameters [12]. ݌ ௜௖ ൌ ܭሾ|ݐሿ ௪௖ (1) Using (1), each intersection node of the structure, P i , with the coordinate of (X i , Y i , Z i ) in the world coordinate system is Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka Ice Load Measurements on Known Structures Using Image Processing Methods S World Academy of Science, Engineering and Technology International Journal of Electrical and Computer Engineering Vol:11, No:8, 2017 920 International Scholarly and Scientific Research & Innovation 11(8) 2017 scholar.waset.org/1307-6892/10007700 International Science Index, Electrical and Computer Engineering Vol:11, No:8, 2017 waset.org/Publication/10007700