A New Fast Fractal Modeling Approach for the Detection of Microcalcifications in Mammograms

In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

Fast Fractal Coding Method for the Detection of Microcalcification in Mammograms

The presence of microcalcifications in mammograms can be considered as an early indication of breast cancer. A fastfractal block coding method to model the mammograms fordetecting the presence of microcalcifications is presented in this paper. The conventional fractal image coding method takes enormous amount of time during the fractal block encoding.procedure. In the proposed method, the image is divided intoshade and non shade blocks based on the dynamic range, andonly non shade blocks are encoded using the fractal encodingtechnique. Since the number of image blocks is considerablyreduced in the matching domain search pool, a saving of97.996% of the encoding time is obtained as compared to theconventional fractal coding method, for modeling mammograms.The above developed mammograms are used for detectingmicrocalcifications and a diagnostic efficiency of 85.7% isobtained for the 28 mammograms used.

A hybrid fractal video compression method

Fractal image compression is a relatively recent image compression method. Its extension to a sequence of motion images is important in video compression applications. There are two basic fractal compression methods, namely the cube-based and the frame-based methods, being commonly used in the industry. However there are advantages and disadvantages in both methods. This paper proposes a hybrid algorithm highlighting the advantages of the two methods in order to produce a good compression algorithm for video industry. Experimental results show the hybrid algorithm improves the compression ratio and the quality of decompressed images.

Adaptive partition and hybrid method in fractal video compression

Fractal image compression is a relatively recent image compression method, which is simple to use and often leads to a high compression ratio. These advantages make it suitable for the situation of a single encoding and many decoding, as required in video on demand, archive compression, etc. There are two fundamental fractal compression methods, namely, the cube-based and the frame-based methods, being commonly studied. However, there are advantages and disadvantages in both methods. This paper gives an extension of the fundamental compression methods based on the concept of adaptive partition. Experimental results show that the algorithms based on adaptive partition may obtain a much higher compression ratio compared to algorithms based on fixed partition while maintaining the quality of decompressed images.

Concise introduction to image processing using C++

A Concise Intro to Image Processing using C++ presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations, and new image compression methods such as fractal image compression and wavelet compression. It includes elementary concepts of image processing and related fundamental tools with coding examples as well as exercises. With a particular emphasis on illustrating fractal and wavelet compression algorithms, the text covers image segmentation, object recognition, and morphology. An accompanying CD-ROM contains code for all algorithms.

Image compression predicated on recurrent iterated function systems

Recurrent iterated function systems (RIFSs) are improvements of iterated function systems (IFSs) using elements of the theory of Marcovian stochastic processes which can produce more natural looking images. We construct new RIFSs consisting substantially of a vertical contraction factor function and nonlinear transformations. These RIFSs are applied to image compression.

分形图像压缩方法研究的新进展

分形图像压缩是一种利用迭代函数系统理论(IFs)、基于自相似特征的有损编码方法。它以其高压缩比的潜在性能而在近年来倍受重视，但目前实现自动IFs编码仍有相当难度，该领域仍存在许多问题亟待解决。笔者对分形图像压缩的理论基础、自动分形图像压缩的实现以及分形图像序列压缩等进行了全面的综述，介绍了各种具有代表性的改进算法，阐明了各个算法的原理和特点，最后对目前研究中存在的问题及可能的对策和研究方向进行了讨论。

资源异质性环境中植物克隆生长的描述与模拟

植物克隆生长型主要由遗传结构决定，不同的克隆植物具有不同的克隆生长型，同时植物的克隆生长型又依具体生境和个体发育阶段不同而变化。Harper认为植物构件的结构由分枝角度、节间长度和芽的成活率决定。大量的研究表明克隆植物生长型主要由3个形态参数决定：节间长度、分枝角度和分枝强度。 植物的生境条件无论在时间还是空间上都是异质性的，即使在很小的尺度上这种异质性也是存在的。在这种具有异质性的生境条件下几乎所有植物都有表型可塑性。植物的表型可塑性是指植物在不同的环境因子条件下，在形态、生物量、生理等方面产生的一系列不同。表现型可塑性是植物种群克服环境异质性的重要途径，也是克隆植物实现觅养行为的途径。克隆植物的觅养行为是通过根茎或匍匐茎的长度和分枝强度的变化以及生物量的分配来实现其迁移和对生境的选择，从而将分株安置在各种微环境中。 克隆植物构型的可塑性可使它在土壤水分斑块性分布的环境中通过克隆生长，调整对不同斑块的土壤水分获取对策。在一田间实验中，匍匐茎草本蛇莓（Duchesnea indica Focke）经历了不同土壤水分水平（土壤最大含水量的40%、60%、80%、100%等）处理，以研究土壤水分对蛇莓克隆构型的影响。结果表明：间隔子长度、分株密度、分枝角度和分枝强度呈二次曲线变化，土壤含水为最大含水量的80%为最适生境。 克隆植物构型的可塑性可使它在养分斑块性分布的环境中通过克隆生长调整相应于对不同斑块的养分获取对策。在一田间实验中，蛇莓经历了不同土壤养分水平（高、中、低和对照）处理，以研究土壤养分对蛇莓克隆构型的影响。结果表明：随着土壤养分水平的增加，间隔子的长度、分枝角度均逐渐降低，分枝强度和分株密度增加。 克隆植物构型的可塑性可使它在不同光强的环境中通过克隆生长，调整其对不同光强的资源获取对策。在控制性光资源异质性生境（模拟浓密林荫、稀疏林荫、农田间套作、裸地等）下，研究和模拟了光资源的时空异质性和蛇莓的克隆可塑性变化。结果表明：随着光照强度的增加，间隔子长度的长度逐渐降低，分枝角度、分株强度呈二次曲线变化。 克隆植物构型的可塑性可使它在不同海拔的环境中通过克隆生长，调整其对不同海拔的资源获取对策。在一海拔高度实验中，匍匐茎草本蛇莓经历了不同海拔(400 m、800 m、1200 m和1600 m)处理，以研究不同海拔对蛇莓克隆构型的影响。结果表明：随着海拔的增加，间隔子长度、分株密度、分枝角度和分枝强度呈二次曲线变化。 从克隆植物生长环境（小气候）定量分析了克隆植物生长必需资源如水分、养分、光强、海拔等的变化特性。具体描述和分析了异质环境尺度的大小和等级数。在前人研究成果的基础上，验证了克隆植物生长必需资源分布异质性的数学模型并建立相应的运算模块。在不同水分、养分、光强和海拔等异质性生境中，蛇莓克隆构型相关特征的可塑性变化可用动态Logistic模型进行模拟和预测，拟合效果较好。结合植物对环境异质性的利用对策，对所揭示的蛇莓克隆构型可塑性进行了讨论。 用分形技术描述了蛇莓在资源斑块性分布的生境中，通过克隆生长调整相应于对不同斑块的资源获取对策。植物克隆构型的形态特征在一定尺度范围内具有自相似特征。蛇莓克隆构型的分形维数直接反映了在异质性生境中蛇莓克隆生长的差异。蛇莓克隆生长越发达分形维数越高。相对小的分形维数，反映出蛇莓克隆生长相对较弱。基于计算机图像技术和分形理论，建立了植物克隆生长分形度量的计算机模型，实现了对植物克隆生长过程的计算机模拟。模拟的蛇莓克隆生长形态与实际生长不仅具有相近的分形维数，而且形态也非常相似。利用克隆生长模型的预测能力克服实验生态学难以逾越的某些研究盲点，其研究成果将对克隆植物利用资源异质性的生态对策研究具有重要的指导意义。

层析静校正技术研究和应用

Static correction is one of the indispensable steps in the conventional onshore seismic data processing, particularly in the western part of China; it is theoretically and practically significant to resolve the issue of static correction. Conventional refraction static correction is put forward under the assumption that layered medium is horizontal and evenly distributed. The complicated nature of the near surface from western part of China is far from the assumption. Therefore, the essential way to resolve the static correction problem from the complex area is to develop a new theory. In this paper, a high-precision non-linear first arrival tomography is applied to solve the problem, it moved beyond the conventional refraction algorithm based on the layered medium and can be used to modeling the complex near surface. Some of the new and creative work done is as follows: One. In the process of first arrival tomographic image modeling, a fast high-order step algorithm is used to calculate the travel time for first arrival and ray path and various factors concerning the fast step ray tracing algorithm is analyzed. Then the second-order and third-order differential format is applied to the step algorithm which greatly increased the calculation precision of the ray tracing and there is no constraint to the velocity distribution from the complex areas. This method has very strong adaptability and it can meet the needs of great velocity variation from the complicated areas. Based on the numerical calculation, a fast high-order step is a fast, non-conditional and stable high-precision tomographic modeling algorithm. Two, in the tomographic inversion, due to the uneven fold coverage and insufficient information, the inversion result is unstable and less reliable. In the paper, wavelet transform is applied to the tomographic inversion which has achieved a good result. Based on the result of the inversion from the real data, wavelet tomographic inversion has increased the reliability and stability of the inversion. Three. Apply the constrained high-precision wavelet tomographic image to the static correction processing from the complex area. During tomographic imaging, by using uphole survey, refraction shooting or other weathering layer method, weathering layer can be identified before the image. Because the group interval for the shot first arrival is relatively big, there is a lack of precision for the near surface inversion. In this paper, an inversion method of the layer constraint and well constraint is put forward, which can be used to compensate the shallow velocity of the inversion for the shot first arrival and increase the precision of the tomographic inversion. Key words: Tomography ，Fast marching method，Wavelet transform, Static corrections, First break

Generating Segmented Quality Meshes from Images

Techniques devoted to generating triangular meshes from intensity images either take as input a segmented image or generate a mesh without distinguishing individual structures contained in the image. These facts may cause difficulties in using such techniques in some applications, such as numerical simulations. In this work we reformulate a previously developed technique for mesh generation from intensity images called Imesh. This reformulation makes Imesh more versatile due to an unified framework that allows an easy change of refinement metric, rendering it effective for constructing meshes for applications with varied requirements, such as numerical simulation and image modeling. Furthermore, a deeper study about the point insertion problem and the development of geometrical criterion for segmentation is also reported in this paper. Meshes with theoretical guarantee of quality can also be obtained for each individual image structure as a post-processing step, a characteristic not usually found in other methods. The tests demonstrate the flexibility and the effectiveness of the approach.

MMM 2005 : proceedings of the 11th International Multimedia Modelling Conference : 12-14 January, 2005, Melbourne, Australia

The International Multimedia Modeling conference series is an annual forum to discuss the efficient representation, processing, interaction, integration, communication, and retrieval of multimedia information.
In particular, the 11th International Multimedia Modeling Conference (MMM2005) concentrates on common modeling frameworks for integrating the diverse fields of visual, audio, video, and virtual world information.
MMM2005 deals with emerging Multimedia Modeling topics that include:
• Audio Analysis and Modeling
• Video Manipulation and Modeling
• Video Mining and MPEG
• Image Modeling and Editing
• Image Retrieval
• Multimedia Presentation and Knowledge Sharing
• AI and Image Recognition
• Mobile and Virtual Multimedia Environments