Expressive rendering: a review of nonphotorealistic techniques

The success of graphics systems that render photorealistic output has obscured parallel developments in nonphotorealistic rendering. A review of these “expressive” systems suggests a framework for further development. One of the authors, Simon Schofield, has developed a prototype system that gives users a wide variety of automatic rendering styles-from the almost photorealistic, through the styles resembling artists' sketches or paintings, to abstract renderings of entirely new forms. The significant problems associated with NPR are primarily aesthetic and only secondarily technical. The culturally oriented theoretical problems surrounding the field are many and, at their most difficult, broach central issues of perception and representation. We therefore begin by discussing the limitations of photorealism as a representational style. However, the technical problems of implementing an NPR system are not trivial. As far as we know, the literature defines no general framework for an NPR system, although it does include an array of more focused solutions. We survey more than 15 of these solutions. On the basis of this survey, we then define a framework for NPR systems that distinguishes them from systems focused on photorealism. We also identify the characteristics of NPR systems that go beyond the tendency to simulate traditional media, functioning instead as 3D renderers. In this context, we briefly describe Schofield's system, called Piranesi, which operates this way     

Deep learning techniques for tumor segmentation: a review

Recently, deep learning, especially convolutional neural networks, has achieved the remarkable results in natural image classification and segmentation. At the same time, in the field of medical image segmentation, researchers use deep learning techniques for tasks such as tumor segmentation, cell segmentation, and organ segmentation. Automatic tumor segmentation plays an important role in radiotherapy and clinical practice and is the basis for the implementation of follow-up treatment programs. This paper reviews the tumor segmentation methods based on deep learning in recent years. We first introduce the common medical image types and the evaluation criteria of segmentation results in tumor segmentation. Then, we review the tumor segmentation methods based on deep learning from technique view and tumor view, respectively. The technique view reviews the researches from the architecture of the deep learning and the tumor view reviews from the type of tumors.

     

Passive image forensics using universal techniques: a review

Digital tamper detection is a substantial research area of image analysis that identifies the manipulation in the image. This domain has matured with time and incredible accuracy in the last five years using machine learning and deep learning-based approaches. Now, it is time for the evolution of fusion and reinforcement-based learning techniques. Nevertheless, before commencing any experimentation, a researcher needs a comprehensive state of the art in that domain. Various directions, their outcome, and analysis form the basis for successful experiments and ensure better results. Universal image forensics approaches are a significant subset of image forensic techniques and must be explored thoroughly before experimentation. This motivated authors to write a review of these approaches. In contrast to the existing recent surveys that aim at image splicing or copy-move detection, our study aims to explore the universal type-independent techniques required to highlight image tampering. Several universal approaches based on resampling, compression, and inconsistency-based detection are compared and evaluated in the presented work. This review communicates the approach used for review, analysed literature, and lastly, the conclusive remarks. Various resources beneficial for the research community, i.e. journals and datasets, are explored and enumerated. Lastly, a futuristic reinforcement learning-based model is proposed.

     

Integration techniques in intelligent operational management: a review

Until recently the concept of an integrated framework for coordinating operational tasks in industrial plants has not been possible due to technological limitations. Integration of functions within an intelligent system architecture would result in improved plant performance, safety and an increase in production. As a result of increased computing power and powerful memory systems, a fully computer integrated system is now possible, however, achieving an integrated framework for operational tasks is quite complex. Problems of task integration include not only the consideration of information flow and timing for a continuously changing environment, but the integration of various problem-solving methodologies. Integration frameworks proposed in the past fail to provide for a fully integrated system. A new approach to accommodate the changing dynamics of a plant's operation is now possible with the Coordinated Knowledge Management method.This paper reviews the components that need to be integrated to encompass intelligent process operation. It also reviews various integration frameworks outlining limitations and presents a proposed method of integration based on knowledge management.     

Advanced optical and magneto-optical recording techniques: a review

Optical data storage is advancing rapidly as we move forward in the 21st Century. Most people today are familiar with CDR and CD-RW as forms of optical data storage, but DVD-R, with considerably higher capacity, will challenge CD-R as the preferred storage medium soon. This review paper looks at the current state of optical recording and some of the current techniques which offer increased magneto-optical storage density, such as Magnetic Super Resolution (MSR), which is already on the market as the GIGAMO disk, and other methods under development. The latter includes Magnetically AMplified Magneto-Optical System (MAMMOS) and Domain Wall Displacement Detection (DWDD). To complement these technologies are a variety of optical techniques, such as near-field recording, which will enable higher storage densities by overcoming the diffraction limit. Holographic storage has promised much over the years, and has largely remained in the research domain. However, new materials and multiplexing techniques show considerable promise for this volumetric storage medium. The overlapping optical and magneto-optical technologies have yielded the concept of hybrid recording and this will also be addressed in this paper. The paper concludes with a look at alternative storage mechanisms, which utilise electronic, as opposed to thermal transitions, to offer improved data rates and improved storage efficiency, and this may dramatically change the way data is stored.David Jenkins would like to thank the Royal Academy of Engineering for financial assistance for attending the Information Storage and Processing Systems Conference where this paper was presented. Paper presented at the 13th Annual Symposium on Information Storage and Processing Systems, Santa Clara, CA, USA, 17–18 June, 2002     

A review of 3D reconstruction techniques in civil engineering and their applications

Three-dimensional (3D) reconstruction techniques have been used to obtain the 3D representations of objects in civil engineering in the form of point cloud models, mesh models and geometric models more often than ever, among which, point cloud models are the basis. In order to clarify the status quo of the research and application of the techniques in civil engineering, literature retrieval is implemented by using major literature databases in the world and the result is summarized by analyzing the abstracts or the full papers when required. First, the research methodology is introduced, and the framework of 3D reconstruction techniques is established. Second, 3D reconstruction techniques for generating point clouds and processing point clouds along with the corresponding algorithms and methods are reviewed respectively. Third, their applications in reconstructing and managing construction sites and reconstructing pipelines of Mechanical, Electrical and Plumbing (MEP) systems, are presented as typical examples, and the achievements are highlighted. Finally, the challenges are discussed and the key research directions to be addressed in the future are proposed. This paper contributes to the knowledge body of 3D reconstruction in two aspects, i.e. summarizing systematically the up-to-date achievements and challenges for the applications of 3D reconstruction techniques in civil engineering, and proposing key future research directions to be addressed in the field.     

Task allocation techniques for distributed computing systems: a review

An efficient strategy to allocate tasks to processors in distributed computer systems is required for proper utilization of available computational power. Various task allocation models developed so far have the basic assumption that an application program is suitably divided into a number of subtasks or modules and the execution costs of modules and intermodule communication costs are also known. The subdivision of a given program into modules is assumed to be carried out by a software mechanism which forms a separate discipline of research work.The task allocation models developed earlier did not consider various constraints like load balancing, precedence relations, timing constraints, etc. Most of the recent works in the formulation of task allocation strategies take into account a number of constraints. This paper presents a brief outline of the various available models and algorithms for task allocation with suggestions for possible future directions in the field.     

Insights into relevant knowledge extraction techniques: a comprehensive review

The Journal of Supercomputing - More than 50 million journal papers will have been published by the end of 2019 with 2 million more journal papers published every year. The number of conference...     

Nighttime visual refinement techniques for surveillance video: a review

Video surveillance systems substitute manual efforts in various safety critic domains such as border area, assisted living, banking, service stations, and transportation. The multimedia-based surveillance system has a significant role in security and forensic systems because people tend to be easily convinced after observing voice, image, and video. Hence, these videos are strong evidence in the forensic investigation. However, most of the criminal activities such as ATM robbery and assassination are occur at nighttime because of the crime supporting dark environment. Many of the night surveillance systems in military, as well as commercial applications, are equipped with infrared and thermal based night vision systems. Its poor capability of texture and color interpretations are the major issues to ensure secure nighttime video monitoring. Specifically, visual refinements of nighttime surroundings and foreground objects provide a valuable assistance in the nighttime security system. In this scenario, it is highly recommended a review of the state-of-the-art nighttime visual refinement approaches. We conducted an extensive literature review and classified the nighttime visual refinement approaches into nighttime restoration and enhancement. This comparative literary analysis identified the research gap fields to explore future research directions in nighttime visual enhancement techniques. Finally, we discussed various open issues and future directions in the context enhancement based nighttime enhancement research.

     

Visual cryptographic techniques for secret image sharing: a review

ABSTRACT

A visual cryptography scheme (VCS) allows one to decrypt images without any knowledge of cryptography and computational efforts. VCS allows secret image sharing such that we can divide the original image into meaningful or nonmeaningful shares. The shares are distributed among participants; during decryption, the original secret image is recovered through stacking all or some of the shares by the human visual system. Various techniques of visual cryptography were constructed mainly for binary images but later, they were enhanced to handle gray-scale or color images. This article focuses on the study of various visual cryptographic schemes and analyses the performance on the basis of various parameters such as, pixel expansion, type of shares generated, image format, number of secret images, encryption method, etc.. In the proposed work, we give a precise and complete review of various visual cryptographic schemes based on different research works related to this area and cite the relevant literature.     

Machine learning: a review of classification and combining techniques

Supervised classification is one of the tasks most frequently carried out by so-called Intelligent Systems. Thus, a large number of techniques have been developed based on Artificial Intelligence (Logic-based techniques, Perceptron-based techniques) and Statistics (Bayesian Networks, Instance-based techniques). The goal of supervised learning is to build a concise model of the distribution of class labels in terms of predictor features. The resulting classifier is then used to assign class labels to the testing instances where the values of the predictor features are known, but the value of the class label is unknown. This paper describes various classification algorithms and the recent attempt for improving classification accuracy—ensembles of classifiers.     

Preview-based techniques for vehicle suspension control: a state-of-the-art review

Automotive suspension systems are key to ride comfort and handling performance enhancement. In the last decades semi-active and active suspension configurations have been the focus of intensive automotive engineering research, and have been implemented by the industry. The recent advances in road profile measurement and estimation systems make road-preview-based suspension control a viable solution for production vehicles. Despite the availability of a significant body of papers on the topic, the literature lacks a comprehensive and up-to-date survey on the variety of proposed techniques for suspension control with road preview, and the comparison of their effectiveness. To cover the gap, this literature review deals with the research conducted over the past decades on the topic of semi-active and active suspension controllers with road preview. The main formulations are reported for each control category, and the respective features are critically analysed, together with the most relevant performance indicators. The paper also discusses the effect of the road preview time on the resulting system performance, and identifies control development trends.     

Surface reconstruction of a two-band crystal: I. Green's function formalism

A Green's function perturbation technique is presented which is appropriate for obtaining the change in the total electronic energy when the surface atoms of a crystal reconstruct in a periodic manner. The phase shift technique is used to determine the change in the density of states. The method is quite general and can be used to study arbitrary reconstructed surfaces. As an illustration, explicit equations appropriate to the (2 × 1) reconstruction of a square lattice are presented.     

Conflict management techniques for model merging: a systematic mapping review

Software and Systems Modeling - Model merging conflicts occur when different stakeholders aim to integrate their contradicting changes that are applied concurrently to update software models. We...     

Image anti-aliasing techniques for Internet visual media processing: a review

Anti-aliasing is a well-established technique in computer graphics that reduces the blocky or stair-wise appearance of pixels. This paper provides a comprehensive overview of the anti-aliasing techniques used in computer graphics, which can be classified into two categories： post-filtering based anti-aliasing and pre-filtering based anti-aliasing. We discuss post-filtering based anti-aliasing algorithms through classifying them into hardware anti-aliasing techniques and post-process techniques for deferred rendering. Comparisons are made among different methods to illustrate the strengths and weaknesses of every category. We also review the utilization ofanti-aliasing techniques from the first category in different graphic processing units, i.e., different NVIDIA and AMD series. This review provides a guide that should allow researchers to position their work in this important research area, and new research problems are identified.     

Review:Image anti-aliasing techniques for Internet visual media processing: a review

Anti-aliasing is a well-established technique in computer graphics that reduces the blocky or stair-wise appearance of pixels. This paper provides a comprehensive overview of the anti-aliasing techniques used in computer graphics, which can be classified into two categories: post-filtering based anti-aliasing and pre-filtering based anti-aliasing. We discuss post-filtering based anti-aliasing algorithms through classifying them into hardware anti-aliasing techniques and post-process techniques for deferred rendering. Comparisons are made among different methods to illustrate the strengths and weaknesses of every category. We also review the utilization of anti-aliasing techniques from the first category in different graphic processing units, i.e., different NVIDIA and AMD series. This review provides a guide that should allow researchers to position their work in this important research area, and new research problems are identified.     

Surface reconstruction by multiaxial triangulation

Outlines for reconstructing object surfaces are traditionally drawn from sequential images in parallel planes. The method presented here instead supports complex object topologies by drawing contours from multiaxial image planes. Multiaxial triangulation of an object in a given data volume involves four steps. First, the user generates contours interactively by selecting sample planes inside the data volume, then drawing object contours from the image corresponding to this sample plane. Our algorithm for multiaxial triangulation then processes these contours to verify consistency within and between sample planes. Second, it uses the sample planes containing the contours to partition the data volume into a divided volume. The contours are partitioned against the plane boundaries, and the contour parts (chains) are associated with faces, edges, and vertices in the divided volume. Third, these chains are joined into closed loops in the divided volume. Fourth, the loops are triangulated patchwise to create the surface model