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Humanoid robots are employed in a wide range of fields to replicate human actions. This paper presents the mechanism, configuration, mathematical modeling, and workspace of a 3D printed humanoid robot – Amaranthine. It also discusses the potential scope of humanoid robots in the present day and future. Robots can be programmed for automation as per the demand of the task or operations to be performed. Humanoid robots, while being one of the small groups of service robots in the current market, have the greatest potential to become the industrial tool of the future. Introducing a Humanoid Robot-like Amaranthine holds huge scope majorly in the fields of medical assistance, teaching aid, large industries where heavy-duty operations require application-specific software, etc. Amaranthine was 3D printed and assembled at the RISC Lab of University of Bridgeport.

Aiming at the detection and tracking of moving targets in industrial automation system, a dynamic target tracking algorithm based on HAAR and CAMSHIFT is proposed. A cascade HAAR classifier is designed and trained for tracking targets. CAMSHIFT algorithm is used to track and detect moving targets quickly. The system is tested on Raspberry Pi embedded platform. The results show that the algorithm can detect the target correctly and track the target effectively.

Visual illusion is the fallacious perception of reality or some actually existing object. In this paper, we imitate the mechanism of Ehrenstein illusion, neon color spreading illusion, watercolor illusion, Kanizsa illusion, shifted edges illusion, and hybrid image illusion using the Open Source Computer Vision Library (OpenCV). We also imitate these illusions using Cellular Neural Networks (CNNs). These imitations suggest that some illusions are processed by high-level brain functions. We next apply the morphological gradient operation to anomalous motion illusions. The processed images are classified into two kinds of images, which correspond to the central drift illusion and the peripheral drift illusion, respectively. It demonstrates that the contrast of the colors plays an important role in the anomalous motion illusion. We also imitate the anomalous motion illusions using both OpenCV and CNN. These imitations suggest that some visual illusions may be processed by the illusory movement of animations.

Humanoid robots are employed in a wide range of fields to replicate human actions. This paper presents the mechanism, configuration, mathematical modeling, and workspace of a 3D printed humanoid robot – Amaranthine. It also discusses the potential scope of humanoid robots in the present day and future. Robots can be programmed for automation as per the demand of the task or operations to be performed. Humanoid robots, while being one of the small groups of service robots in the current market, have the greatest potential to become the industrial tool of the future. Introducing a Humanoid Robot-like Amaranthine holds huge scope majorly in the fields of medical assistance, teaching aid, large industries where heavy-duty operations require application-specific software, etc. Amaranthine was 3D printed and assembled at the RISC Lab of University of Bridgeport.

Due to the increasing number of accidents happening when flying target landing in the weapon testing field, a smart video surveillance system based on moving target recognition was designed. The system adopts the capturing front-server-decision model. In our paper, a method for detecting moving targets images using background difference method and frame difference method is first introduced. Secondly, target recognition is studied by the technology of contour extraction and edge detection. Finally, characteristic parameters of target are extracted by feature algorithm. Based on it, key technologies involved in the system are described in detail. Additionally, corresponding algorithm is designed using OpenCV in Visual C++ 6.0, and part of the key codes are given. Simulation results shows that the system designed can meet the needs of monitor and control of flying target, and also verify the effectiveness of the algorithm.

In this paper, an algorithm based on monocular vision is applied into length measurement on plane and the process of extracting corner using OpenCV are introduced in detail. This algorithm is realized using OpenCV 2.4.9 and Visual Studio 2013. Firstly, extract all the target corners on chessboard using OpenCV functions. Then calculate the model parameters consisting of extrinsic and intrinsic parameters of camera with the use of the least square method and the corners extracted. Coordinates of all the points on chessboard can be obtained by its image coordinates and the model parameters correspondently. Thereby, positions of target points and length can be measured. In our experiment, the relative error of the positioning is less than 2%. The result proves the feasibility of the algorithm.