Embedded video stabilization system on field programmable gate array for unmanned aerial vehicle

Unmanned Aerial Vehicles (UAVs) equipped with lightweight and low-cost cameras have grown in popularity and enable new applications of UAV technology. However, the video retrieved from small size UAVs is normally in low-quality due to high frequency jitter. This thesis presents the development of video stabilization algorithm implemented on Field Programmable Gate Array (FPGA). The video stabilization algorithm consists of three main processes, which are motion estimation, motion stabilization and motion compensation to minimize the jitter. Motion estimation involves block matching and Random Sample Consensus (RANSAC) to estimate the affine matrix that defines the motion perspective between two consecutive frames. Then, parameter extraction, motion smoothing and motion vector correction, which are parts of the motion stabilization, are tasked in removing unwanted camera movement. Finally, motion compensation stabilizes two consecutive frames based on filtered motion vectors. In order to facilitate the ground station mobility, this algorithm needs to be processed onboard the UAV in real-time. The nature of parallelization of video stabilization processing is suitable to be utilized by using FPGA in order to achieve real-time capability. The implementation of this system is on Altera DE2-115 FPGA board. Full hardware dedicated cores without Nios II processor are designed in stream-oriented architecture to accelerate the computation. Furthermore, a parallelized architecture consisting of block matching and highly parameterizable RANSAC processor modules show that the proposed system is able to achieve up to 30 frames per second processing and a good stabilization improvement up to 1.78 Interframe Transformation Fidelity value. Hence, it is concluded that the proposed system is suitable for real-time video stabilization for UAV application

An Efficient Threshold Based Mixed Noise Removal Technique

Removing or reducing noises from image is very important task in image processing. This paper presents an efficient noise removal technique to restore original digital images corrupted by mixed noise. The proposed filtering technique consists of three steps: noisy pixel detection using fuzzy flag, mixed noise filtering step and calculating threshold value remove the pixel value with replacement conditions. Noises in this methodology are the combination of gaussian noise and salt and pepper noise. This methodology reduces the mixed noise without lossing edges sharpness and information. This methodology gives better results existing many fuzzy algorithms. The proposed technique shows better peak signal noise ratio result with thresholding replacement conditions. Hence, this mixed noise removal technique finds application in numerous segments of image process like digital tv, medical image process, camera, police work systems etc. Wiener filter is used for image enhancement

Measurements, Models, Systems and Design

531 s.

Machine vision applications in UAVs for autonomous aerial refueling and runway detection

This research focuses on the application of Machine Vision (MV) techniques and algorithms to the problems of Autonomous Aerial Refueling (AAR) and Runway Detection. In particular, real laboratory based hardware was used in a simulated environment to emulate real-life conditions for AAR. It was shown that the K-Means Clustering Algorithm solution to the Marker Detection problem could be executed at a frame rate of 30 Hz and it averaged a tracking error of less than one pixel while utilizing only 0.16% of the image. It was also shown that the solution to the Runway Detection problem could be executed at a frame rate of 20 Hz which is acceptable for use in an UAV performing reconnaissance work. Data from these tests suggest that both software schemes are suitable for applications in moving vehicles and that the accuracy of the measurements produced by the schemes make them suitable for UAV applications

Liver segmentation using marker controlled watershed transform

The largest organ in the body is the liver and primarily helps in metabolism and detoxification. Liver segmentation is a crucial step in liver cancer detection in computer vision-based biomedical image analysis. Liver segmentation is a critical task and results in under-segmentation and over-segmentation due to the complex structure of abdominal computed tomography (CT) images, noise, and textural variations over the image. This paper presents liver segmentation in abdominal CT images using marker-based watershed transforms. In the pre-processing stage, a modified double stage gaussian filter (MDSGF) is used to enhance the contrast, and preserve the edge and texture information of liver CT images. Further, marker controlled watershed transform is utilized for the segmentation of liver images from the abdominal CT images. Liver segmentation using suggested MDSGF and marker-based watershed transform help to diminish the under-segmentation and over-segmentation of the liver object. The performance of the proposed system is evaluated on the LiTS dataset based on Dice score (DS), relative volume difference (RVD), volumetric overlapping error (VOE), and Jaccard index (JI). The proposed method gives (Dice score of 0.959, RVD of 0.09, VOE of 0.089, and JI of 0.921)

高速ビジョンを用いたリアルタイムビデオモザイキングと安定化に関する研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs