We review multilevel hierarchies under two special aspects: their potential for abstraction and for storing discrete representations. Motivated by claims to ‘bridge the representational gap between image and model fe...
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Aiming at the cu rrent structured P2P system's locality of physical location and accessing resources, in the context of P4P technology, this paper takes the Pastry algorithm as a foundation, proposes a P4P routing...
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In this paper we propose a novel method for the construction of invariant textural features for grey scale images. The textural features are based on an averaging over the 2D Euclidean transformation group with relati...
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To meet the challenge of implementing rapidly advanced, time-consuming medical imageprocessing algorithms, it is necessary to develop a medical imageprocessing technology to process a 2D or 3D medical image dynamica...
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To meet the challenge of implementing rapidly advanced, time-consuming medical imageprocessing algorithms, it is necessary to develop a medical imageprocessing technology to process a 2D or 3D medical image dynamically on the web. But in a premier system, only static imageprocessing can be provided with the limitation of web technology. The development of Java and CORBA (common object request broker architecture) overcomes the shortcoming of the web static application and makes the dynamic processing of medical images on the web available. To develop an open solution of distributed computing, we integrate the Java, and web with the CORBA and present a web-based medical image dynamic processing methed, which adopts Java technology as the language to program application and components of the web and utilies the CORBA architecture to cope with heterogeneous property of a complex distributed system. The method also provides a platform-independent, transparent processing architecture to implement the advanced image routines and enable users to access large dataset and resources according to the requirements of medical applications. The experiment in this paper shows that the medical image dynamic processing method implemented on the web by using Java and the CORBA is feasible.
Analysis on the basis of the protocol Gnutella0.6, the use P4P technologies for sensing conveniently network topology information, proposes a P4P-based Gnutella routing algorithm, in which nodes join algorithm to cons...
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Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans, which can be generally classified into disease related mutations and common ones. It has been generally accepted that SNPs ...
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Pupil localization is a very important preprocessing step in many machine vision applications. Accurate and robust pupil localization especially in non-ideal eye images (such as images with defocusing, motion blur, oc...
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ISBN:
(纸本)9784901122078
Pupil localization is a very important preprocessing step in many machine vision applications. Accurate and robust pupil localization especially in non-ideal eye images (such as images with defocusing, motion blur, occlusion etc.) is a challenging task. In this paper, a detailed method to solve this problem is proposed. This method is implemented in three main steps: first, segment the rough pupil region based on Gaussian Mixture Model according to the gray level distribution of eye image;then modify the rough segmentation result using morphological method to minimize the influence of some disturbing factors;last step is to estimate the pupil parameters based on minimizing the least square error. The proposed method is first tested on CASIA iris image dataset, and then on our self-captured iris dataset which with more varieties. Experiments show that the proposed method can perform well for non-ideal eye images of various qualities.
In many branches of industry, piled box-like objects have to be recognized, grasped and transferred. Unfortunately, existing systems only deal with the most simple configurations (i.e. neatly placed boxes) effectively...
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This paper proposes an automatic salient object extraction framework. Firstly, the saliency model are developed by applying the low level color features and the boundary prior. The initial salient regions are extracte...
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Iris image quality assessment is an important part of iris recognition system because the qualities of iris images would largely influence the recognition results. In this paper, we analyze and compare several represe...
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ISBN:
(纸本)9784901122078
Iris image quality assessment is an important part of iris recognition system because the qualities of iris images would largely influence the recognition results. In this paper, we analyze and compare several representative quality assessment methods, and then propose an effective method based on Laplacian of Gaussian operator for iris image assessment. Through computer simulations of several typical algorithms on our iris image database, SJTU-IDB, the proposed method is shown superior to the compared quality assessment methods.
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