排序方式: 共有11条查询结果,搜索用时 15 毫秒
1.
Paavola M. Kamarainen M. Jarvinen J.A.M. Saukoski M. Laiho M. Halonen K.A.I. 《Solid-State Circuits, IEEE Journal of》2007,42(12):2651-2665
In this paper, a micropower interface IC for a capacitive 3-axis micro-accelerometer implemented in a 0.13- BiCMOS process is presented. The sensor interface consists of a front-end that converts the acceleration signal to voltage, two algorithmic ADCs, two frequency references, and a voltage, current, and temperature reference circuit. Die area and power dissipation are reduced by using time-multiplexed sampling and varying duty cycles down to 0.3%. The chip with a 0.51 active area draws 62 from a 1.8 V supply while sampling temperature at 100 Hz, and four proof masses, each at 1.04 kHz. With a 4-g capacitive 3-axis accelerometer, the measured noise floors in the x-, y-, and z-directions are 482 , 639 , and 662 , respectively. 相似文献
2.
Invariant object recognition is one of the most central problems in computer vision. To be successful when occlusion and distortions are present, object recognition has to be based on local features. The features should express the significant information while being robust in the presence of noise and distortions, and stable in terms of feature parameters. In this study, Gabor filtering based features is analyzed in terms of the above requirements. Two classes of Gabor features are introduced: global Gabor features and fundamental frequency Gabor features. The Gabor filter response and stability issues are analyzed in terms of the filtering parameters. The robustness of the proposed features is examined through experiments. Both analytical and experimental results indicate that when certain conditions on the filter parameters are met, Gabor filtering can be reliably used in low-level feature extraction in image processing, and the filter responses can be used to construct robust invariant recognition systems. 相似文献
3.
T. Kauppi J. K. Kamarainen L. Lensu H. Kälviäinen H. Uusitalo 《Pattern Recognition and Image Analysis》2011,21(2):140-143
This invited paper considers the results of the IMAGERET project. The goal of the project is to demonstrate how lesions in
a retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. The project
consists of the following results: an image annotation tool for medical expert annotation, diabetic retinopathy databases,
an evaluation framework for development and comparison of methods, image-based and pixel-based methods, and new imaging solutions.
The automated diagnosis can be seen in two steps: in the first step, it is decided whether an eye needs further analysis (too
many lesions visible) or not (the eye is healthy enough). In the second step, fundus images selected for further analysis
are automatically diagnosed. The developed system saves both resources of medical experts and costs in healthcare. It will
further offer a tool for the health care providers to improve the quality of the life of diabetes patients. This is important
since the number of diabetes patients is increasing, especially rapidly in the developed countries. 相似文献
4.
5.
Pouria Babahajiani Lixin Fan Joni-Kristian Kämäräinen Moncef Gabbouj 《Machine Vision and Applications》2017,28(7):679-694
3D urban maps with semantic labels and metric information are not only essential for the next generation robots such autonomous vehicles and city drones, but also help to visualize and augment local environment in mobile user applications. The machine vision challenge is to generate accurate urban maps from existing data with minimal manual annotation. In this work, we propose a novel methodology that takes GPS registered LiDAR (Light Detection And Ranging) point clouds and street view images as inputs and creates semantic labels for the 3D points clouds using a hybrid of rule-based parsing and learning-based labelling that combine point cloud and photometric features. The rule-based parsing boosts segmentation of simple and large structures such as street surfaces and building facades that span almost 75% of the point cloud data. For more complex structures, such as cars, trees and pedestrians, we adopt boosted decision trees that exploit both structure (LiDAR) and photometric (street view) features. We provide qualitative examples of our methodology in 3D visualization where we construct parametric graphical models from labelled data and in 2D image segmentation where 3D labels are back projected to the street view images. In quantitative evaluation we report classification accuracy and computing times and compare results to competing methods with three popular databases: NAVTEQ True, Paris-Rue-Madame and TLS (terrestrial laser scanned) Velodyne. 相似文献
6.
Ilonen J. Kamarainen J.-K. Lindh T. Ahola J. Kalviainen H. Partanen J. 《Industry Applications, IEEE Transactions on》2005,41(4):963-971
In the modern industrial environment there is increasing demand for automatic condition monitoring. With reliable condition monitoring, faults such as mechanical motor failures could be identified in their early stages and further damage to the system could be prevented. Successful monitoring is a complex and application-specific problem, but a generic tool would be useful in preliminary analysis of new signals and in verification of known theories. A generic condition diagnosis tool is introduced in this paper. The tool is based on discriminative energy functions which reveal discriminative frequency-domain regions where failures can be identified. The tool was applied to induction motor bearing fault detection and succeeded in finding characteristic frequencies which allow accurate detection of bearing faults. 相似文献
7.
Alexander Drobchenko Joni-Kristian Kamarainen Lasse Lensu Jarkko Vartiainen Heikki K?lvi?inen Tuomas Eerola 《Frontiers of Electrical and Electronic Engineering in China》2011,6(2):328-338
Fine and sparse details appear in many quality inspection applications requiring machine vision. Especially on flat surfaces,
such as paper or board, the details can be made detectable by oblique illumination. In this study, a general definition of
such details is given by defining sufficient statistical properties from histograms. The statistical model allows simulation
of data and comparison of methods designed for detail detection. Based on the definition, utilization of the existing thresholding
methods is shown to be well motivated. The comparison shows that minimum error thresholding outperforms the other standard
methods. Finally, the results are successfully applied to a paper printability inspection application, and the IGT picking
assessment, in which small surface defects must be detected. The provided method and measurement system prototype provide
automated assessment with results comparable to manual expert evaluations in this laborious task. 相似文献
8.
An evolutionary optimization method over continuous search spaces, differential evolution, has recently been successfully
applied to real world and artificial optimization problems and proposed also for neural network training. However, differential
evolution has not been comprehensively studied in the context of training neural network weights, i.e., how useful is differential
evolution in finding the global optimum for expense of convergence speed. In this study, differential evolution has been analyzed
as a candidate global optimization method for feed-forward neural networks. In comparison to gradient based methods, differential
evolution seems not to provide any distinct advantage in terms of learning rate or solution quality. Differential evolution
can rather be used in validation of reached optima and in the development of regularization terms and non-conventional transfer
functions that do not necessarily provide gradient information.
This revised version was published online in June 2006 with corrections to the Cover Date. 相似文献
9.
Jarkko Vartiainen Albert Sadovnikov Joni-Kristian Kamarainen Lasse Lensu Heikki Kälviäinen 《Machine Vision and Applications》2008,19(4):249-259
Regular patterns, as defined in this study, are found in areas of industry and science, for example, halftone raster patterns
used in the printing industry and crystal lattice structures in solid state physics. The need for quality inspection of products
containing regular patterns has aroused interest in the application of machine vision for automatic inspection. Quality inspection
typically corresponds to detecting abnormalities, defined as irregularities in this case. In this study, the problem of irregularity
detection is described in analytical form and three different detection methods are proposed. All the methods are based on
characteristics of the Fourier transform to compactly represent regular information. The Fourier transform enables the separation
of regular and irregular parts of an input image. The three methods presented are shown to differ in their generality and
computational complexities. 相似文献
10.
Feature-based affine-Invariant localization of faces 总被引:1,自引:0,他引:1
Hamouz M Kittler J Kamarainen JK Paalanen P Kälviäinen H Matas J 《IEEE transactions on pattern analysis and machine intelligence》2005,27(9):1490-1495
We present a novel method for localizing faces in person identification scenarios. Such scenarios involve high resolution images of frontal faces. The proposed algorithm does not require color, copes well in cluttered backgrounds, and accurately localizes faces including eye centers. An extensive analysis and a performance evaluation on the XM2VTS database and on the realistic BioID and BANCA face databases is presented. We show that the algorithm has precision superior to reference methods. 相似文献