15 research outputs found

    Color Image Watermarking using JND Sampling Technique

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    This paper presents a color image watermarking scheme using Just Noticeable Difference (JND) Sampling Technique in spatial domain. The nonlinear JND Sampling technique is based on physiological capabilities and limitations of human vision. The quantization levels have been computed using the technique for each of the basic colors R, G and B respectively for sampling color images. A watermark is scaled to half JND image and is added to the JND sampled image at known spatial position. For transmission of the image over a channel, the watermarked image has been represented using Reduced Biquaternion (RB) numbers. The original image and the watermark are retrieved using the proposed algorithms. The detection and retrieval techniques presented in this paper have been quantitatively benchmarked with a few contemporary algorithms using MSE and PSNR. The proposed algorithms outperform most of them. Keywords: Color image watermarking, JND sampling, Reduced Biquaternion, Retrieva

    Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics

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    This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p

    Optimization techniques for computationally expensive rendering algorithms

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    Realistic rendering in computer graphics simulates the interactions of light and surfaces. While many accurate models for surface reflection and lighting, including solid surfaces and participating media have been described; most of them rely on intensive computation. Common practices such as adding constraints and assumptions can increase performance. However, they may compromise the quality of the resulting images or the variety of phenomena that can be accurately represented. In this thesis, we will focus on rendering methods that require high amounts of computational resources. Our intention is to consider several conceptually different approaches capable of reducing these requirements with only limited implications in the quality of the results. The first part of this work will study rendering of time-­¿varying participating media. Examples of this type of matter are smoke, optically thick gases and any material that, unlike the vacuum, scatters and absorbs the light that travels through it. We will focus on a subset of algorithms that approximate realistic illumination using images of real world scenes. Starting from the traditional ray marching algorithm, we will suggest and implement different optimizations that will allow performing the computation at interactive frame rates. This thesis will also analyze two different aspects of the generation of anti-­¿aliased images. One targeted to the rendering of screen-­¿space anti-­¿aliased images and the reduction of the artifacts generated in rasterized lines and edges. We expect to describe an implementation that, working as a post process, it is efficient enough to be added to existing rendering pipelines with reduced performance impact. A third method will take advantage of the limitations of the human visual system (HVS) to reduce the resources required to render temporally antialiased images. While film and digital cameras naturally produce motion blur, rendering pipelines need to explicitly simulate it. This process is known to be one of the most important burdens for every rendering pipeline. Motivated by this, we plan to run a series of psychophysical experiments targeted at identifying groups of motion-­¿blurred images that are perceptually equivalent. A possible outcome is the proposal of criteria that may lead to reductions of the rendering budgets

    Compression, Modeling, and Real-Time Rendering of Realistic Materials and Objects

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    The realism of a scene basically depends on the quality of the geometry, the illumination and the materials that are used. Whereas many sources for the creation of three-dimensional geometry exist and numerous algorithms for the approximation of global illumination were presented, the acquisition and rendering of realistic materials remains a challenging problem. Realistic materials are very important in computer graphics, because they describe the reflectance properties of surfaces, which are based on the interaction of light and matter. In the real world, an enormous diversity of materials can be found, comprising very different properties. One important objective in computer graphics is to understand these processes, to formalize them and to finally simulate them. For this purpose various analytical models do already exist, but their parameterization remains difficult as the number of parameters is usually very high. Also, they fail for very complex materials that occur in the real world. Measured materials, on the other hand, are prone to long acquisition time and to huge input data size. Although very efficient statistical compression algorithms were presented, most of them do not allow for editability, such as altering the diffuse color or mesostructure. In this thesis, a material representation is introduced that makes it possible to edit these features. This makes it possible to re-use the acquisition results in order to easily and quickly create deviations of the original material. These deviations may be subtle, but also substantial, allowing for a wide spectrum of material appearances. The approach presented in this thesis is not based on compression, but on a decomposition of the surface into several materials with different reflection properties. Based on a microfacette model, the light-matter interaction is represented by a function that can be stored in an ordinary two-dimensional texture. Additionally, depth information, local rotations, and the diffuse color are stored in these textures. As a result of the decomposition, some of the original information is inevitably lost, therefore an algorithm for the efficient simulation of subsurface scattering is presented as well. Another contribution of this work is a novel perception-based simplification metric that includes the material of an object. This metric comprises features of the human visual system, for example trichromatic color perception or reduced resolution. The proposed metric allows for a more aggressive simplification in regions where geometric metrics do not simplif

    Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)

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    The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment. FMER is a subset of image processing and it is a multidisciplinary topic to analysis. So, it requires familiarity with other topics of Artifactual Intelligence (AI) such as machine learning, digital image processing, psychology and more. So, it is a great opportunity to write a book which covers all of these topics for beginner to professional readers in the field of AI and even without having background of AI. Our goal is to provide a standalone introduction in the field of MFER analysis in the form of theorical descriptions for readers with no background in image processing with reproducible Matlab practical examples. Also, we describe any basic definitions for FMER analysis and MATLAB library which is used in the text, that helps final reader to apply the experiments in the real-world applications. We believe that this book is suitable for students, researchers, and professionals alike, who need to develop practical skills, along with a basic understanding of the field. We expect that, after reading this book, the reader feels comfortable with different key stages such as color and depth image processing, color and depth image representation, classification, machine learning, facial micro-expressions recognition, feature extraction and dimensionality reduction. The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment.Comment: This is the second edition of the boo

    Connected Attribute Filtering Based on Contour Smoothness

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