116 research outputs found

    The modelling of natural imperfections and an improved space filling curve halftoning technique.

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    by Tien-tsin Wong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1994.Includes bibliographical references (leaves 72-79).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- The Modelling of Natural Imperfections --- p.1Chapter 1.2 --- Improved Clustered-dot Space Filling Curve Halftoning Technique --- p.2Chapter 1.3 --- Structure of the Thesis --- p.3Chapter 2 --- The Modelling of Natural Imperfections --- p.4Chapter 2.1 --- Introduction --- p.4Chapter 2.2 --- Related Work --- p.6Chapter 2.2.1 --- Texture Mapping --- p.6Chapter 2.2.2 --- Blinn's Dusty Surfaces --- p.7Chapter 2.2.3 --- Imperfection Rule-based Systems --- p.7Chapter 2.3 --- Natural Surface Imperfections --- p.8Chapter 2.3.1 --- Dust Accumulation --- p.8Chapter 2.3.2 --- Scratching --- p.10Chapter 2.3.3 --- Rusting --- p.10Chapter 2.3.4 --- Mould --- p.11Chapter 2.4 --- New Modelling Framework for Natural Imperfections --- p.13Chapter 2.4.1 --- Calculation of Tendency --- p.13Chapter 2.4.2 --- Generation of Chaotic Pattern --- p.19Chapter 2.5 --- Modelling of Dust Accumulation --- p.21Chapter 2.5.1 --- Predicted Tendency of Dust Accumulation --- p.22Chapter 2.5.2 --- External Factors --- p.24Chapter 2.5.3 --- Generation of Fuzzy Dust Layer --- p.30Chapter 2.5.4 --- Implementation Issues --- p.31Chapter 2.6 --- Modelling of Scratching --- p.31Chapter 2.6.1 --- External Factor --- p.32Chapter 2.6.2 --- Generation of Chaotic Scratch Patterns --- p.35Chapter 2.6.3 --- Implementation Issues --- p.36Chapter 3 --- An Improved Space Filling Curve Halftoning Technique --- p.39Chapter 3.1 --- Introduction --- p.39Chapter 3.2 --- Review on Some Halftoning Techniques --- p.41Chapter 3.2.1 --- Ordered Dither --- p.41Chapter 3.2.2 --- Error Diffusion and Dither with Blue Noise --- p.42Chapter 3.2.3 --- Dot Diffusion --- p.43Chapter 3.2.4 --- Halftoning Along Space Filling Traversal --- p.43Chapter 3.2.5 --- Space Diffusion --- p.46Chapter 3.3 --- Improvements on the Clustered-Dot Space Filling Halftoning Method --- p.47Chapter 3.3.1 --- Selective Precipitation --- p.47Chapter 3.3.2 --- Adaptive Clustering --- p.50Chapter 3.4 --- Comparison With Other Methods --- p.57Chapter 3.4.1 --- Low Resolution Observations --- p.57Chapter 3.4.2 --- High Resolution Printing Results --- p.58Chapter 3.4.3 --- Analytical Comparison --- p.58Chapter 4 --- Conclusion and Future Work --- p.69Chapter 4.1 --- The Modelling of Natural Imperfections --- p.69Chapter 4.2 --- An Improved Space Filling Curve Halftoning Technique --- p.71Bibliography --- p.7

    Floating Points: A Method for Computing Stipple Drawings

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    An importance driven genetic algorithm for the halftoning process

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    Most evolutionary approaches to halftoning techniques have been concerned with the paramount goal of halftoning: achieving an accurate reproduction of local grayscale intensities while avoiding the introduction of artifacts. A secondary concern in halftoning has been the preservation of edges in the halftoned image. In this paper, we will introduce a new evolutionary approach through the use of an importance function. This approach has at least two main characteristics. First, it can produce results similar to many other halftoning techniques. Second, if the chosen importance function is accordingly changed, areas of the image with high variance can be highlighted.III Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

    QR-RLS algorithm for error diffusion of color images

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    Printing color images on color printers and displaying them on computer monitors requires a significant reduction of physically distinct colors, which causes degradation in image quality. An efficient method to improve the display quality of a quantized image is error diffusion, which works by distributing the previous quantization errors to neighboring pixels, exploiting the eye's averaging of colors in the neighborhood of the point of interest. This creates the illusion of more colors. A new error diffusion method is presented in which the adaptive recursive least-squares (RLS) algorithm is used. This algorithm provides local optimization of the error diffusion filter along with smoothing of the filter coefficients in a neighborhood. To improve the performance, a diagonal scan is used in processing the image, (C) 2000 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(00)00611-5]

    Survey on Securing Medical Image Transmission using Visual Cryptography Techniques

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    Visual cryptography scheme is a cryptographic technique which allows visual information text or image to be encrypted in such a way that the decryption can be performed by the human visual system and without the aid of computers. It encodes the secret image into shares of different patterns. Visual Cryptography is done on black and white image as well as on color image. This paper includes the literature survey regarding Visual Cryptography techniques for secure medical image transmission

    Novel methods in image halftoning

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    Ankara : Department of Electrical and Electronics Engineering and Institute of Engineering and Science, Bilkent Univ., 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 97-101Halftoning refers to the problem of rendering continuous-tone (contone) images on display and printing devices which are capable of reproducing only a limited number of colors. A new adaptive halftoning method using the adaptive QR- RLS algorithm is developed for error diffusion which is one of the halftoning techniques. Also, a diagonal scanning strategy to exploit the human visual system properties in processing the image is proposed. Simulation results on color images demonstrate the superior quality of the new method compared to the existing methods. Another problem studied in this thesis is inverse halftoning which is the problem of recovering a contone image from a given halftoned image. A novel inverse halftoning method is developed for restoring a contone image from the halftoned image. A set theoretic formulation is used where sets are defined using the prior information about the problem. A new space domain projection is introduced assuming the halftoning is performed ,with error diffusion, and the error diffusion filter kernel is known. The space domain, frequency domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution. Simulation results for both grayscale and color images give good results, and demonstrate the effectiveness of the proposed inverse halftoning method.Bozkurt, GözdeM.S

    A Benchmarking assessment of known visual cryptography algorithms

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    With the growth of digital media, it is becoming more prevalent to find a method to protect the security of that media. An effective method for securely transmitting images is found in the field of Visual Cryptography. While this method is effective for securely transmitting images, many methods have been developed since the first algorithm was proposed in 1994 by Naor and Shamir. A benchmarking scheme is proposed to give the algorithm capabilities, understand the implementation method, evaluate the algorithm development, and provide image reconstruction information. Additionally, the algorithms are ranked according to a Visual Cryptography standard. This would allow an easy way to differentiate between algorithms and determine the ideal algorithm for a given task or project

    Scanning and Sequential Decision Making for Multidimensional Data -- Part II: The Noisy Case

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    We consider the problem of sequential decision making for random fields corrupted by noise. In this scenario, the decision maker observes a noisy version of the data, yet judged with respect to the clean data. In particular, we first consider the problem of scanning and sequentially filtering noisy random fields. In this case, the sequential filter is given the freedom to choose the path over which it traverses the random field (e.g., noisy image or video sequence), thus it is natural to ask what is the best achievable performance and how sensitive this performance is to the choice of the scan. We formally define the problem of scanning and filtering, derive a bound on the best achievable performance, and quantify the excess loss occurring when nonoptimal scanners are used, compared to optimal scanning and filtering. We then discuss the problem of scanning and prediction for noisy random fields. This setting is a natural model for applications such as restoration and coding of noisy images. We formally define the problem of scanning and prediction of a noisy multidimensional array and relate the optimal performance to the clean scandictability defined by Merhav and Weissman. Moreover, bounds on the excess loss due to suboptimal scans are derived, and a universal prediction algorithm is suggested. This paper is the second part of a two-part paper. The first paper dealt with scanning and sequential decision making on noiseless data arrays

    Scanning and Sequential Decision Making for Multi-Dimensional Data - Part I: the Noiseless Case

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    We investigate the problem of scanning and prediction ("scandiction", for short) of multidimensional data arrays. This problem arises in several aspects of image and video processing, such as predictive coding, for example, where an image is compressed by coding the error sequence resulting from scandicting it. Thus, it is natural to ask what is the optimal method to scan and predict a given image, what is the resulting minimum prediction loss, and whether there exist specific scandiction schemes which are universal in some sense. Specifically, we investigate the following problems: First, modeling the data array as a random field, we wish to examine whether there exists a scandiction scheme which is independent of the field's distribution, yet asymptotically achieves the same performance as if this distribution was known. This question is answered in the affirmative for the set of all spatially stationary random fields and under mild conditions on the loss function. We then discuss the scenario where a non-optimal scanning order is used, yet accompanied by an optimal predictor, and derive bounds on the excess loss compared to optimal scanning and prediction. This paper is the first part of a two-part paper on sequential decision making for multi-dimensional data. It deals with clean, noiseless data arrays. The second part deals with noisy data arrays, namely, with the case where the decision maker observes only a noisy version of the data, yet it is judged with respect to the original, clean data.Comment: 46 pages, 2 figures. Revised version: title changed, section 1 revised, section 3.1 added, a few minor/technical corrections mad
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