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Noise is an un-expected signal which exists naturally at any system. In the study of fractal batik coloring, noise as a spot is generated as the basis of batik motive coloring. Even distribution of noise spots will produce art-works which involve elements of culture and technology. The development of batik motives and colors could be harmonized with the development of technology, such as the use of fractal method in order to create the new motives of batik. Fractal is a geometric form which can be separated into pieces, where each part is the repeated small version. The coloring of batik was based on the generating noise using Gaussian method. Noise on fractal batik was spots which were generated randomly on the surface of fractal batik, meanwhile Gaussian method was a noise model which followed normal distribution standard with zero average and standard deviation 1.The generating noise as coloring basis of fractal batik patterns, which was formed in the previous study, showed the distant error of noise between 9.1 pixels and 13.7 pixels. This was because the distribution of noise on the fractal batik patterns was carried out randomly using Gaussian method for every process of fractal rewriting system.
By applying Fourier Transformation, this paper shows that batik has fractal characteristic. This character is shown in batik's fractal dimension between 1 and 2. The isen process in batik is one factor that contributes to create self affine as one of fractal's important characteristic. Anova Test for fractal dimension in this method classifies batik according to patterns and its region. Fractal in batik shows the presence of complexity in traditional art. This complexity arises because the effort to obey pakem rule (symbolic meaning, mystical, harmony, symmetry) and media limitation (canting, wax, textiles). Furthermore, the presence of fractal in batik becomes the foundation of this paper to create algoryhtm which will produce new kind of patterns: Batik Fractal. The method used for creating the pattern is L-System and Fractal Dimension. L-System is used to create pattern, while Fractal Dimension is used as a measurement tool for Batik Fractal to compare with traditional batik. Algorithm to create Batik Fractal has been developed into a software known as jBatik. jBatik is a software to generate batik pattern, making it a tool to create generative art. As a software, jBatik becomes a helping tool for batik makers to create new patterns. jBatik is an innovation and addition to help batik makers. jBatik v 2.0 has been used as a tool to create new batik patterns in creative industry by involving several batik makers. jBatik has also been used extensively by Batik Fractal to create new batik patterns.
We present a simple optical system for producing self-similar fractal patterns. The key component comprises three adjacent lenses, which form multiple images of a pattern displayed on a monitor. The images are recorded by a camera and displayed as the new pattern on the monitor. Iteration of this process results in an approximation to a self-similar fractal pattern which is independent of the starting image.
Mathematical models applied to urban and regional planning have been widely developed during the sixties. Since that time
the scientific and technologic developments have deeply transformed the field of spatial modelling. There has been a reaction
against the idea that reality could be reduced to deterministic models. The paradigms of complexity, chaos, self-organisation,
fractal geometry have made obvious the unpredictability of complex socio-economic systems. At the same time the progress of
computation has led to the substitution of simulation methods to analytic solutions of mathematical models. In such a context,
models are loosing in generality and reproducibility what they earn in adaptation to empirical situations. An important challenge
is also to confirm the pertinence and specificity of the geographical approach. In that respect the spatial analysis programs
must prove the evidence of a common methodology dealing either with physical or human and economic domain. We are working,
for instance, on cellular automata programs applied to the historical evolution of an urban space and also to the run-off
process in an elementary basin. The spatial structure of the models may be slightly different: rectangular or hexagonal tessellations
in the “Human Geography” program, TIN structure, closer to the physical reality, in the other. The relations between the cells
may also differ: they are often defined by a distance matrix for the socio-economic models, but a contiguity matrix is of
course needed for the streaming process. But, beyond these technical differences, it appears that the geographical programs
are developed on a macro-level, that is on aggregate statistical units. The elementary particle is always (or should be for
a geographer...) a material, spatial unit, unlike the drop of water of the hydrologists, or the individual “agents” of the
sociologists' multi-agents systems. The difference between the micro and macro level is not a question of scale, but a difference
of logic. The simulation approach has a requisite, which is a need of systematic validation by a permanent comparison with
the actual situation, but the objective is not prediction. The scientific concern is, before all, a precise understanding
of the past and recent evolutions, more than a forecasting, which escapes to the specific field of scientific research. What
is scientific is what can be measured. The possible prediction may rely on the scientific research, but belongs strictly to
the domain of intellectual and personal thinking.
The production of organ parenchyma in a rapid and reproducible manner is critical to normal development. In chimeras produced by the combination of genetically distinguishable tissues, mosaic patterns of cells derived from the combined genotypes can be visualized. These patterns comprise patches of contiguously similar genotypes and are different in different organs but similar in a given organ from individual to individual. Thus, the processes that produce the patterns are regulated and conserved. We have previously established that mosaic patches in multiple tissues are fractal, consistent with an iterative, recursive growth model with simple stereotypical division rules. Fractal dimensions of various tissues are consistent with algorithmic models in which changing a single variable (e.g. daughter cell placement after division) switches the mosaic pattern from islands to stripes of cells. Here we show that the spiral pattern previously observed in mouse cornea can also be visualized in rat chimeras. While it is generally held that the pattern is induced by stem cell division dynamics, there is an unexplained discrepancy in the speed of cellular migration and the emergence of the pattern. We demonstrate in chimeric rat corneas both island and striped patterns exist depending on the age of the animal. The patches that comprise the pattern are fractal, and the fractal dimension changes with the age of the animal and indicates the constraint in patch complexity as the spiral pattern emerges. The spiral patterns are consistent with a loxodrome. Such data are likely to be relevant to growth and cell division in organ systems and will help in understanding how organ parenchyma are generated and maintained from multipotent stem cell populations located in specific topographical locations within the organ. Ultimately, understanding algorithmic growth is likely to be essential in achieving organ regeneration in vivo or in vitro from stem cell populations.
This paper describes an evolutionary art system, which explores the potential ability of evolutionary computation in Batik
design. We investigate the use of Interactive Evolutionary Algorithm (IEA) in our system, with the goal of enhancing user’s
creativity to generate innovative Batik-like patterns. We focus mainly on two crucial aspects of the system. First, a new
representation is proposed to capture the features in Batik and create innovative patterns through evolutionary processes.
Second, an out-breeding mechanism is applied to our system, in order to sustain user’s interest for a longer period. Our system
can search a much larger design space than other systems and can avoid being trapped in a local optimum. We describe the system
in detail and the methodology we have adopted in the system. Our experimental results have shown that our newly developed
system is effective and has great potentials in evolving novel Batik design.
Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.
A fractal tiling or f-tiling is a tiling which possesses self-similarity and the boundary of which is a fractal. In this paper, we investigate the classification of fractal tilings with kite-shaped and dart-shaped prototiles from which three new f-tilings are found. Invariant mappings are constructed for the creation of aesthetic patterns on such tilings. A modified convergence time scheme is described, which reflects the rate of convergence of various orbits and at the same time, enhances the artistic appeal of a generated image. A scheme based on the frequency of visit at a pixel is used to generate chaotic attractors.
The high-speed connection of 3G network has transferred cell-phone applications’ bottleneck from network speed to both the performance of hardware and software and the presentational layer of applications. The 3D visualization on search results for mobile search client can meet the needs of 3G new business. And this technology can be widely used in the areas such as product display, advertising, real estate and the game industry. This paper took searching buildings for the real estate field as an example. Firstly the parallel computing was introduced to enhance the process of modeling calculation and rendering for 3D building model. Then search result presented in the form of 3D visualization on the user interface of mobile search. Finally, the experiment emulated the post-drawing 3D building on mobile phone. And the simulation result showed that the 3D building was displayed in high-speed rate, and changed smoothly with a strong sense of 3D.
A new and fast algorithm is presented in this paper for the automatic generation of aesthetic patterns on nonperiodic tilings by means of dynamical systems. The Chair and the Sphinx tilings are used as illustrations. Invariant mappings are constructed for the creation of striking patterns on these tilings. A modified convergence time scheme is described to enhance the artistic appeal of generated images. This algorithm can be used to create a great variety of exotic patterns with various nonperiodicities.
a b s t r a c t A new approach (FBI) describing the enzymatic browning kinetics for three apple cultivars, is presented. It is based on quantification of the irregular color patterns that emerge from the apple surface during enzymatic browning, rather than using the color average in the same area analyzed. In the experiments, three apple cultivars slices were placed under a computer vision system and color digital images were captured. The images were transformed to Lab space color using a quadratic transformation function and the Fourier fractal texture image was used to calculate a fractal dimension value (FD), in order to rep-resent the complexity of lightness intensity distribution (L) over the surface. FD (proposed method) and the mean L value (traditional method) were used indistinctly (as a fractional conversion) to model the enzymatic kinetic using the power-law model. The results showed that the fractal theory can be used to describe the browning kinetic and to distinguish apple cultivars, based on their browning sensitivity under the same experimental conditions. Enzymatic browning rates derived using the fractal kinetic method, were between 14.3 and 23.2 times (in absolute value) higher than the rates calculated with the traditional method. The fractional first-order model was established only for kinetics calculated using the traditional method.
In this work, a new method is proposed to the widely neglected problem of Arabic font recognition, it uses global texture analysis. This method is based on fractal geometry, and the feature extraction does not depend on the document contents. In our method, we take the document as an image containing some specific textures and regard font recognition as texture identification.We have combined both techniques BCD (box counting dimension) and DCD (dilation counting dimension) to obtain the main features. The first expresses texture distribution in 2-D image. The second makes possible to take on the human vision system aspect, since it makes it possible to differentiate one font from another. Both features are expressed in a parametric form; then four features were kept. Experiments are carried out by using 1000 samples of 10 typefaces (each typeface is combined with four sizes). The average recognition rates are of about 96.2% using KNN (K nearest neighbor) and 98% using RBF (radial basic function). Experimental results are also included in the robustness of the method against written size, skew, image degradation (e.g., Gaussian noise) and resolution, and compared with the existing methods. The main advantages of our method are that (1) the dimension of feature vector is very low; (2) the variation sizes of the studied blocks (which are not standardized) are robust; (3) less samples are needed to train the classifier; (4) finally and the most important, is the first attempt to apply and adapt fractal dimensions to font recognition.
The calculation of the fractal dimension is crucial in fractal geometry. The popular approach is based on box-counting. However, this scheme is easily disturbed by noise and produces many non-negligible plateaus that cause an underestimation. This paper proposes a more robust and efficient method for computing the fractal dimension. To validate its performance, a feature vector based on fractal dimension and M-band wavelet transform was applied to the classification of natural textured images and ultrasonic liver images based on four different classifiers. The experimental results revealed the proposed computation method is trustworthy.
The fractal dimension has been studied as a feature for texture analysis. It has been found that the fractal dimension is not an effective image texture measure but little is known about the reasons for the fractal dimension failing to be effective for texture analysis. This paper investigates into the underlying causes why the fractal dimension is not an effective image texture feature. Four mathematical properties have been identified which are responsible for the fractal dimension's ineffectiveness. The experimental results show that while the fractal dimension itself is hardly an effective feature for texture classification, it can considerably enhance other feature sets.
This paper proposes biometric-based fractal pattern classifier for fingerprint recognition using grey relational analysis (GRA). Fingerprint patterns have arch, loop, whorl, and accidental morphologys, and embed singular points, which result in establishing fingerprint individuality. An automatic fingerprint identification system consists of three stages: image acquisition and processing, feature extraction, and pattern recognition. Fingerprint images are captured from subjects using an optical fingerprint reader (OFR). Digital image preprocessing (DIP) is used to refine out noise, enhance the image, convert to binary image, and locate the reference point. For binary images, Katz’s algorithm is employed to estimate the fractal dimension (FD) from two-dimension (2D) image. Biometric characteristics are extracted as fractal patterns using Weierstrass cosine function (WCF) with different FDs. GRA performs to compare the fractal patterns among the small-scale database. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.
This paper presents a novel and non-destructive approach to the appearance characterization and classification of commercial pork, turkey and chicken ham slices. Ham slice images were modelled using directional fractal (DF(0°;45°;90°;135°)) dimensions and a minimum distance classifier was adopted to perform the classification task. Also, the role of different colour spaces and the resolution level of the images on DF analysis were investigated. This approach was applied to 480 wafer thin ham slices from four types of hams (120 slices per type): i.e., pork (cooked and smoked), turkey (smoked) and chicken (roasted). DF features were extracted from digitalized intensity images in greyscale, and R, G, B, L(∗), a(∗), b(∗), H, S, and V colour components for three image resolution levels (100%, 50%, and 25%). Simulation results show that in spite of the complexity and high variability in colour and texture appearance, the modelling of ham slice images with DF dimensions allows the capture of differentiating textural features between the four commercial ham types. Independent DF features entail better discrimination than that using the average of four directions. However, DF dimensions reveal a high sensitivity to colour channel, orientation and image resolution for the fractal analysis. The classification accuracy using six DF dimension features (a(90°)(∗),a(135°)(∗),H(0°),H(45°),S(0°),H(90°)) was 93.9% for training data and 82.2% for testing data.
Image analysis has gained new effort in the scientific community due to the chance of investigating morphological properties of three dimensional structures starting from their bi-dimensional gray-scale representation. Such ability makes it particularly interesting for tissue engineering (TE) purposes. Indeed, the capability of obtaining and interpreting images of tissue scaffolds, extracting morphological and structural information, is essential to the characterization and design of engineered porous systems. In this work, the traditional image analysis approach has been coupled with a probabilistic based percolation method to outline a general procedure for analysing tissue scaffold SEM micrographs. To this aim a case study constituted by PCL multi-scaled porous scaffolds was adopted. Moreover, the resulting data were compared with the outputs of conventionally used techniques, such as mercury intrusion porosimetry. Results indicate that image processing methods well fit the porosity features of PCL scaffolds, overcoming the limits of the more invasive porosimetry techniques. Also the cut off resolution of such IP methods was discussed. Moreover, the fractal dimension of percolating clusters, within the pore populations, was addressed as a good indication of the interconnection degree of PCL bi-modal scaffolds. Such findings represent (i) the bases for a novel approach complementary to the conventional experimental procedure used for the morphological analysis of TE scaffolds, in particular offering a valid method for the analysis of soft materials (i.e., gels); also (ii) providing a new perspective for further studies integrating to the structural and morphological data, fluid-dynamics and transport properties modelling.
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generation algorithms continue to be invented, or is there some “universal” algorithm that can generate all (and only) the perceptually distinguishable images, or even all members of a restricted class of patterns such as logos or letterforms? In fact there are many complete algorithms that can generate all possible images, but most images are random and not perceptually distinguishable. Counting arguments show that the percentage of distinguishable images that will be generated by such complete algorithms is vanishingly small. In this paper we observe that perceptually distinguishable images are compressible. Using this observation it is evident that algorithmic complexity provides an appropriate framework for discussing the question of a universal image generator. We propose a natural Thesis for describing perceptually distinguishable images and argue its validity. Based on it, we show that there is no program that generates all (and only) these images. Although this is an abstract result, it may have import for several areas in graphics that deal with compressible signals. In essence, new representations and pattern generation algorithms will continue to be developed; there is no feasible “super algorithm” that is capable of all things.
Computer Graphic with Visual C ++ and OpenGL v.6
- Suyoto
Suyoto, Computer Graphic with Visual C ++ and
OpenGL v.6. (in Bahasa), Yogyakarta: Gava Media,
2003.
Computer Graphic with J2ME? (in Bahasa)
- Suyoto
Suyoto, "Computer Graphic with J2ME? (in Bahasa),"
Jurnal AiTI, II (2), 2005.
Fractal Applications on Mobile Phones with J2ME? (in Bahasa)
- Suyoto
Suyoto, "Fractal Applications on Mobile Phones with
J2ME? (in Bahasa)," Jurnal Teknologi Industri, X (2),
2006.
The Model of Searching Digital Image on Database Image using the Approach of Color Pattern Proximity Calculation
- A S Aribowo
A. S. Aribowo, "The Model of Searching Digital Image
on Database Image using the Approach of Color Pattern
Proximity Calculation.," in Seminar Nasional
Informatika, Yogyakarta, 2009.
Pengenalan Ucapan Dengan Jaringan Saraf Tiruan Kohonen
- L Sumarno
- E Harjanti
L. Sumarno and E. Harjanti, "Pengenalan Ucapan
Dengan Jaringan Saraf Tiruan Kohonen," Jurnal
SIGMA, Program Studi Teknik Elektro, Fakultas
Teknik Universitas Sanata Dharma, VIII (2), pp. 117-
125, 2005.
Pengidentifikasian Pembuat Tulisan Tangan Dengan Pengenalan Pola Biomimetik
- Samsuyardi
Samsuyardi, "Pengidentifikasian Pembuat Tulisan
Tangan Dengan Pengenalan Pola Biomimetik," Jurnal
Generik Fakultas Ilmu Komputer Universitas Sriwijaya,
IV (2), pp. 31-33, 2009.