Image watermarking, steganography, and morphological processing

With the fast development of computer technology, research in the fields of multimedia security, image processing, and robot vision have recently become popular. Image watermarking, steganogrphic system, morphological processing and shortest path planning are important subjects among them. In this dissertation, the fundamental techniques are reviewed first followed by the presentation of novel algorithms and theorems for these three subjects. The research on multimedia security consists of two parts, image watermarking and steganographic system. In image watermarking, several algorithms are developed to achieve different goals as shown below. In order to embed more watermarks and to minimize distortion of watermarked images, a novel watermarking technique using combinational spatial and frequency domains is presented. In order to correct rounding errors, a novel technique based on the genetic algorithm (GA) is developed. By separating medical images into Region of Interest (ROI) and non-ROI parts, higher compression rates can be achieved where the ROI is compressed by lossless compression and the non-ROI by lossy compression. The GA-based watermarking technique can also be considered as a fundamental platform for other fragile watermarking techniques. In order to simplify the selection and integrate different watermarking techniques, a novel adjusted-purpose digital watermarking is developed. In order to enlarge the capacity of robust watermarking, a novel robust high-capacity watermarking is developed. In steganographic system, a novel steganographic algorithm is developed by using GA to break the inspection of steganalytic system. In morphological processing, the GA-based techniques are developed to decompose arbitrary shapes of big binary structuring elements and arbitrary values of big grayscale structuring elements into small ones. The decomposition is suited for a parallel-pipelined architecture. The techniques can speed up the morphological processing and allow full freedom for users to design any type and any size of binary and grayscale structuring elements. In applications such as shortest path planning, a novel method is first presented to obtaining Euclidean distance transformation (EDT) in just two scans of image. The shortest path can be extracted based on distance maps by tracking minimum values. In order to record the motion path, a new chain-code representation is developed to allow forward and backward movements. By placing the smooth turning-angle constraint, it is possible to mimic realistic motions of cars. By using dynamically rotational morphology, it is not only guarantee collision-free in the shortest path, but also reduce time complexity dramatically. As soon as the distance map of a destination and collision-free codes have been established off-line, shortest paths of cars given any starting location toward the destination can be promptly obtained on-line

AVstack: An Open-Source, Reconfigurable Platform for Autonomous Vehicle Development

Pioneers of autonomous vehicles (AVs) promised to revolutionize the driving experience and driving safety. However, milestones in AVs have materialized slower than forecast. Two culprits are (1) the lack of verifiability of proposed state-of-the-art AV components, and (2) stagnation of pursuing next-level evaluations, e.g., vehicle-to-infrastructure (V2I) and multi-agent collaboration. In part, progress has been hampered by: the large volume of software in AVs, the multiple disparate conventions, the difficulty of testing across datasets and simulators, and the inflexibility of state-of-the-art AV components. To address these challenges, we present AVstack, an open-source, reconfigurable software platform for AV design, implementation, test, and analysis. AVstack solves the validation problem by enabling first-of-a-kind trade studies on datasets and physics-based simulators. AVstack solves the stagnation problem as a reconfigurable AV platform built on dozens of open-source AV components in a high-level programming language. We demonstrate the power of AVstack through longitudinal testing across multiple benchmark datasets and V2I-collaboration case studies that explore trade-offs of designing multi-sensor, multi-agent algorithms

Scenic: A Language for Scenario Specification and Scene Generation

We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the problems of training a perception system to handle rare events, testing its performance under different conditions, and debugging failures. We show how a probabilistic programming language can help address these problems by specifying distributions encoding interesting types of inputs and sampling these to generate specialized training and test sets. More generally, such languages can be used for cyber-physical systems and robotics to write environment models, an essential prerequisite to any formal analysis. In this paper, we focus on systems like autonomous cars and robots, whose environment is a "scene", a configuration of physical objects and agents. We design a domain-specific language, Scenic, for describing "scenarios" that are distributions over scenes. As a probabilistic programming language, Scenic allows assigning distributions to features of the scene, as well as declaratively imposing hard and soft constraints over the scene. We develop specialized techniques for sampling from the resulting distribution, taking advantage of the structure provided by Scenic's domain-specific syntax. Finally, we apply Scenic in a case study on a convolutional neural network designed to detect cars in road images, improving its performance beyond that achieved by state-of-the-art synthetic data generation methods.Comment: 41 pages, 36 figures. Full version of a PLDI 2019 paper (extending UC Berkeley EECS Department Tech Report No. UCB/EECS-2018-8

Physics of Transport and Traffic Phenomena in Biology: from molecular motors and cells to organisms

Traffic-like collective movements are observed at almost all levels of biological systems. Molecular motor proteins like, for example, kinesin and dynein, which are the vehicles of almost all intra-cellular transport in eukayotic cells, sometimes encounter traffic jam that manifests as a disease of the organism. Similarly, traffic jam of collagenase MMP-1, which moves on the collagen fibrils of the extracellular matrix of vertebrates, has also been observed in recent experiments. Traffic-like movements of social insects like ants and termites on trails are, perhaps, more familiar in our everyday life. Experimental, theoretical and computational investigations in the last few years have led to a deeper understanding of the generic or common physical principles involved in these phenomena. In particular, some of the methods of non-equilibrium statistical mechanics, pioneered almost a hundred years ago by Einstein, Langevin and others, turned out to be powerful theoretical tools for quantitaive analysis of models of these traffic-like collective phenomena as these systems are intrinsically far from equilibrium. In this review we critically examine the current status of our understanding, expose the limitations of the existing methods, mention open challenging questions and speculate on the possible future directions of research in this interdisciplinary area where physics meets not only chemistry and biology but also (nano-)technology.Comment: 33 page Review article, REVTEX text, 29 EPS and PS figure

A RULE-BASED APPROACH TO ANIMATING MULTI-AGENT ENVIRONMENTS

This dissertation describes ESCAPE (Expert Systems in Computer Animation Production Environments), a multi-agent animation system for building domain-oriented, rule-based visual programming environments. Much recent work in computer graphics has been concerned with producing behavioural animations of artificial life-forms mainly based on algorithmic approaches. This research indicates how, by adding an inference engine and rules that describe such behaviour, traditional computer animation environments can be enhanced. The comparison between using algorithmic approaches and using a rule-based approach for representing multi-agent worlds is not based upon their respective claims to completeness, but rather on the ease with which end users may express their knowledge and control their animations with a minimum of technical knowledge. An environment for the design of computer animations incorporating an expert system approach is described. In addition to direct manipulation of objects on the screen, the environment allows users to describe behavioural rules based upon both the physical and non-physical attributes of objects. These rules can be interpreted to suggest the transition from stage to stage or to automatically produce a longer animation. The output from the system can be integrated into a commercially available 3D modelling and rendering package. Experience indicates that a hybrid environment, mixing algorithmic and rule-based approaches, would be very promising and offer benefits in application areas such as creating realistic background scenes and modelling human beings or animals either singly or in groups. A prototype evaluation system and three different domains are described and illustrated with preliminary animated images

Virtual reality application for automotive design reviews

During this work the objective is to create a visualization application in Unreal Engine 5 that is able to improve the current issues that are faced every day by artists that perform design reviews in Virtual Reality. The scope of this project is limited to the context of the Spanish car company called SEAT where the practical project has been developed. The target user for the program that will be developed is the professional artists that create the different parts of the car. They would ideally use it whenever there is a review to be made. The opportunity to access the car design facilities and work with the technology they implement has come from a 6 months internship at the company. The project has been developed in 3 stages: preproduction, where the major part of the research takes place and the program’s interface will be designed; production, the stage where the program is implemented; and postproduction, where the validation with industry professionals takes place. After completing the project, the feedback has been great but there are still some steps to take to get to the point of having a complete product that could be used professionally for design reviews. The application works as expected with stable performance that does not induce any sickness and an intuitive interaction system that is easy to learn. When car models are complete, they have millions of polygons and complex materials applied to them so it is difficult to find a balance between quality and performance for the design review sessions. Moreover, natural interfaces are still being researched and are not commonly integrated into the widespread VR applications so there is still a lot of work to be done in that regard