Probabilistic pseudo-morphology for grayscale and color images

Mathematical morphology offers popular image processing tools, successfully used for binary and grayscale images. Recently, its extension to color images has become of interest and several approaches were proposed. Due to various issues arising from the vectorial nature of the data, none of them imposed as a generally valid solution. We propose a probabilistic pseudo-morphological approach, by estimating two pseudo-extrema based on Chebyshev inequality. The framework embeds a parameter which allows controlling the linear versus non-linear behavior of the probabilistic pseudo-morphological operators. We compare our approach for grayscale images with the classical morphology and we emphasize the impact of this parameter on the results. Then, we extend the approach to color images, using principal component analysis. As validation criteria, we use the estimation of the color fractal dimension, color textured image segmentation and color texture classification. Furthermore, we compare our proposed method against two widely used approaches, one morphological and one pseudo-morphological.     

Catalyst surface at a fractal of cost—a quest for optimal catalyst loading

Intuition tells us that any decrease in the catalytically active surface area should result in an equivalent decrease in the reaction yield and efficiency. Our findings counter this by showing that the active surface and hence the catalyst loading can be reduced drastically in the diffusion-limited heterogeneous reaction systems, while the conversion rate remains essentially unchanged by using fractals for spatial distribution of the catalyst load. The results of this study provide an unusual circumstance for optimal design of chemically active surfaces and can be used to drastically reduce cost of heterogeneous chemical and biological reactors, sensors, and electrodes of fuel cells. The proposed approach can be exploited to its fullest extent in chemical microsystems by utilizing the latest advances in our abilities to manipulate matter on the micro/nano scale.     

Fractal characterization for the mining crack evolution process of overlying strata based on microseismic monitoring technology

In order to study the evolution laws during the development process of the coal face overburden rock mining-induced fissure,we studied the process of evolution of overburden rock mining-induced fissures and dynamically quantitatively described its fractal laws,based on the high-precision microseismic monitoring method and the nonlinear Fractal Geometry Theory.The results show that:the overburden rock mining-induced fissure fractal dimension experiences two periodic change processes with the coal face advance,namely a Small→ Big→ Small process,which tends to be stable;the functional relationship between the extraction step distance and the overburden rock mining-induced fissure fractal dimension is a cubic curve.The results suggest that the fractal dimension reflects the evolution characteristics of the overburden rock mining-induced fissure,which can be used as an evaluation index of the stability of the overburden rock strata,and it provides theoretical guidance for stability analysis of the overburden rock strata,goaf roof control and the support movements in the mining face.     

声发射源特征识别的最新方法

介绍多传感器数据融合、时频能量模式分析及分析理论识别声发射源特征的方法，说明基于波形分析的现代信号处理技术是揭示声发射源及信号传播规律的重要手段。     

Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants.     

基于Agent的分形供应链自适应协同计算

应用分形、智能Ａｇｅｎｔ和神经网络自适应控制技术,研究分形供应链适应环境变化的结构模式和策略模式．探讨了分形供应链Ａｇｅｎｔ关联结构,提出了分形供应链双层自适应协同计算模式,论述了资源Ａｇｅｎｔ,信息协调Ａｇｅｎｔ,人机交互Ａｇｅｎｔ和领域计算Ａｇｅｎｔ之间的相互作用关系．以一个分形模块的策略协同为分析对象,研究了领域单元的自适应协同计算模式,分析了分形模块的成本模型,并对基于Ａｇｅｎｔ交互的神经网络模型部分进行了算例仿真．     

Valuations,regular expressions,and fractal geometry

Valuations — morphisms from ( _n ^* ,·,) to ((0, ), ·, 1) — are a simple generalization of so-called Bernoulli morphisms. In this paper, we show a characterization of strongly unambiguous regular expressions with the help of valuations and formal power series. We apply these algebraic results to the determination of Hausdorff dimensions of fractals described by regular expressions.     

Real time fractal image coder based on characteristic vector matching

Fractal coding algorithm has many applications including image compression. In this paper a classification scheme is presented which allows the hardware implementation of the fractal coder. High speed and low power consumption are the goal of the suggested design. The introduced method is based on binary classification of domain and range blocks. The proposed technique increases the processing speed and reduces the power consumption while the qualities of the reconstructed images are comparable with those of the available software techniques. In order to show the functionality of the proposed algorithm, the architecture was implemented on a FPGA chip. The application of the proposed hardware is shown in image compression. The resulted compression ratios, PSNR error, gate count, compression speed and power consumption are compared with the existing designs. Other applications of the proposed design are feasible in certain fields such as mass–volume database coding and also in video coder’s block matching schemes.     

A fast MATLAB program to estimate the multifractal spectrum of multidimensional data: Application to fractures

A MATLAB^® program based on the Hou algorithm for estimation of fractal dimension and multifractal spectrum of fractures is presented. The program performance was tested with many synthetical fractals and field data. Interpolation and sampling effects on the fractal dimension and multifractal spectrum estimation were also studied. Some common problems related to the fractal dimension and multifractal spectrum are also discussed.     

植物三维建模方综述

A series of plant’s 3D modeling methods are introduced in this paper.They include fractal modeling method,A-system,particle system,L-system,layer based modeling method, mcdeling method faithtul to botanical structure and development and interactive modeling method.This will be helpful in the future research of plant’s 3D model.