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conference on machine vision applications, Architectures, and Systems Integration vi

作者： Casasent, D Talukder, A Lee, HW Carnegie Mellon Univ. (United States) Dongyang Univ. (South Korea)

ISBN: (纸本)0819426377

processing of real-time X-ray images of randomly-oriented and touching pistachio nuts for product inspection is considered. We describe the image processing used to isolate individual nuts (segmentation). This involves a new watershed transform algorithm. Segmentation results on approximately 3000 X-ray (film) and real time X-ray (linescan) nut images were excellent (> 99.9% correct). Initial classification results on film images are presented that indicate that the percentage of infested nuts can be reduced to 1.6% of the crop with only 2% of the good nuts rejected;this performance is much better than present manual methods and other automated classifiers have achieved.

关键词： classification detection morphological processing product inspection watershed transform segmentation X-ray sensors

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An elliptic phase-shift algorithm for high speed three-dimensional profilometry

An elliptic phase-shift algorithm for high speed three-dimen...

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conference on image processing - machine vision applications vi

作者： Deng, Fuqin Li, Zhao Chen, Jia Deng, Jiangwen Fung, Kenneth S. M. Lam, Edmund Y. Univ Hong Kong Dept Elect & Elect Engn Imaging Syst Lab Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9780819494344

A high throughput is often required in many machine vision systems, especially on the assembly line in the semiconductor industry. To develop a non-contact three-dimensional dense surface reconstruction system for real-time surface inspection and metrology applications, in this work, we project sinusoidal patterns onto the inspected objects and propose a high speed phase-shift algorithm. First, we use an illumination-reflectivity-focus (IRF) model to investigate the factors in image formation for phase-measuring profilometry. Second, by visualizing and analyzing the characteristic intensity locus projected onto the intensity space, we build a two-dimensional phase map to store the phase information for each point in the intensity space. Third, we develop an efficient elliptic phase-shift algorithm (E-PSA) for high speed surface profilometry. In this method, instead of calculating the time-consuming inverse trigonometric function, we only need to normalize the measured image intensities and then index the built two-dimensional phase map during real-time phase reconstruction. Finally, experimental results show that it is about two times faster than conventional phase-shift algorithm.

关键词： Three-dimensional image acquisition phase-shift algorithm industrial inspection surface measurements profilometry

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On the design of a flexible image processing library in C++

On the design of a flexible image processing library in C++

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conference on machine vision applications, Architectures, and Systems Integration vi

作者： Sacha, JP Shabestari, BN Kohler, TA Advanced Imaging Group Edison Industrial Systems Center Toledo OH 43607 1700 N. Westwood Canada

ISBN: (纸本)0819426377

There are two crucial, complementary, issues faced during design and implementation of practically any but a simple image processing library. First is an ability to represent a variety of image types, typically the discriminate feature being the pixel type, e.g. binary, short integer, long integer, or floating point. The second issue is implementation of image processing algorithms that will be able to operate on each of the supported image representations. In many traditional library designs this leads to reimplementation of the same algorithm many times, once for each possible image representation. Some attempts to alleviate this problem introduce elaborate schemes of dynamic pixel representation and registration. This results in single algorithm implementation, however, due to dynamic pixel registration, efficiency of these implementations is poor. In this paper, we investigate use of parameterized algorithms and design issues involved in implementing them in C++. We permit single expression of the algorithm to be used with any concrete representation of an image. Use of advanced features of C++ and object-oriented programming allow us to use static pixel representations, where pixel types are resolved during compile time instead of run time. This approach leads to very flexible and efficient implementations. We have both advantages: single algorithm implementation for numerous image representations, and best possible speed of execution.

关键词： image processing library parametric algorithms generalized image processing notation object-oriented programming

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Efficient Defect Detection with Sign Information of Walsh Hadamard Transform

Efficient Defect Detection with Sign Information of Walsh Ha...

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conference on image processing - machine vision applications vi

作者： Zhang, Qiang van Beek, Peter Yuan, Chang Xu, Xinyu Seo, Hae-jong Li, Baoxin Arizona State Univ Tempe AZ 85281 USA

ISBN: (纸本)9780819494344

We propose a method for defect detection based on taking the sign information of Walsh Hadamard Transform (WHT) coefficients. The core of the proposed algorithm involves only three steps that can all be implemented very efficiently: applying the forward WHT, taking the sign of the transform coefficients, and taking an inverse WHT using only the sign information. Our implementation takes only 7 milliseconds for a 512 x 512 image on a PC platform. As a result, the proposed method is more efficient than the PHase Only Transform (PHOT) method and other methods in literature. In addition, the proposed approach is capable of detecting defects of varying shapes, by combining the 2-dimensional WHT and 1-dimensional WHT;and can detect defects in images with strong object boundaries by utilizing a reference image. The proposed algorithm is robust over different background image patterns and varying illumination conditions. We evaluated the proposed method both visually and quantitatively and obtained good results on images from various defect detection applications.

关键词： Defect Detection Walsh Hadamard Transform Sign Information PHase Only Transform image Signature

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CONFORMAL COMPUTATIONAL GEOMETRY FOR machine vision.

NATO Conference Series, (Series) 4: Marine Sciences

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NATO conference Series, (Series) 4: Marine Sciences 1980年 2卷 1106-1110页

作者： Chaikin, George M. Weiman, Carl F.R.

A novel computational geometry architecture for image processing and display applications is described, based upon the logarithmic conformal mapping of a pixel space. Parallel algorithms for image rotation, scaling and translation are given. Examples illustrating applications to the extraction of three dimensional structural information and the discrete Fourier transform are given.

关键词： image processing

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Coherent image Layout using an Adaptive visual Vocabulary

Coherent Image Layout using an Adaptive Visual Vocabulary

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conference on image processing - machine vision applications vi

作者： Dillard, Scott E. Henry, Michael J. Bohn, Shawn Gosink, Luke J. Pacific NW Natl Lab Richland WA 99352 USA

ISBN: (纸本)9780819494344

When querying a huge image database containing millions of images, the result of the query may still contain many thousands of images that need to be presented to the user. We consider the problem of arranging such a large set of images into a visually coherent layout, one that places similar images next to each other. image similarity is determined using a bag-of-features model, and the layout is constructed from a hierarchical clustering of the image set by mapping an in-order traversal of the hierarchy tree into a space-filling curve. This layout method provides strong locality guarantees so we are able to quantitatively evaluate performance using standard image retrieval benchmarks. Performance of the bag-of-features method is best when the vocabulary is learned on the image set being clustered. Because learning a large, discriminative vocabulary is a computationally demanding task, we present a novel method for efficiently adapting a generic visual vocabulary to a particular dataset. We evaluate our clustering and vocabulary adaptation methods on a variety of image datasets and show that adapting a generic vocabulary to a particular set of images improves performance on both hierarchical clustering and image retrieval tasks.

关键词： image Browsing Hierarchical Clustering Bag of Features

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MONO-MODAL image REGISTRATION viA CORRENTROPY MEASURE

MONO-MODAL IMAGE REGISTRATION VIA CORRENTROPY MEASURE

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8th Iranian conference on machine vision and image processing (MviP)

作者： Ghaffari, A. Fatemizadeh, E. Sharif Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781467361842

The registration of images is a fundamental task in numerous applications in medical image processing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure as similarity measure in mono modal setting. Correntropy is a important measure between two random variables based on information theoretic learning and kernel methods. This measure is useful in nonGaussian signal processing. In this paper, this measure is used in image registration. Here, we analytically illustrate that this measure is robust in presence of spiky noise (impulsive noise). The experimental results show that the proposed similarity has better performance than traditional intensity-based similarity measures such as Mutual information and SSD.

关键词： image registration similarity measure Correntropy spiky noise Free Form Deformation

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Automated detection of Karnal bunt teliospores

Automated detection of Karnal bunt teliospores

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conference on machine vision applications in Industrial Inspection vi

作者： Linder, KD Baumgart, C Creager, J Heinen, B Troupe, T Meyer, D Carr, J Quint, J Allied Signal Fed Mfg & Technol Albuquerque NM 87196 USA

ISBN: (纸本)0819427462

Karnal bunt is a fungal disease which infects wheat and, when present in wheat crops, yields it unsatisfactory for human consumption. Due to the fact that Karnal bunt (KB) is difficult to detect in the field, samples are taken to laboratories where technicians use microscopes and methodically search for KB teliospores. AlliedSignal Federal Manufacturing & Technologies (FM&T), working with the Kansas Department of Agriculture, created a system which utilizes pattern recognition, feature extraction, and neural networks to prototype an automated detection system for identifying KB teliospores. System hardware consists of a biological compound microscope, motorized stage, CCD camera, frame grabber, and a PC. Integration of the system hardware with custom software comprises the machine vision system. Fundamental processing steps involve capturing an image from the slide, while concurrently processing the previous image. Features extracted from the acquired imagery are then processed by a neural network classifier which has been trained to recognize "spore-like" objects. images with "spore-like" objects are reviewed by trained technicians. Benefits of this system include: (1) reduction of the overall cycle-time;(2) utilization of technicians for intelligent decision making (vs. manual searching);(3) a regulatory standard which is quantifiable and repeatable;(4) guaranteed 100% coverage of the cover slip;and (5) significantly enhanced detection accuracy.

关键词： image processing neural network machine vision

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Eliminating illumination effects by discrete cosine transform (DCT) coefficients' attenuation and accentuation

Eliminating illumination effects by discrete cosine transfor...

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conference on image processing - machine vision applications vi

作者： Du, Shan Shehata, Mohamed Badawy, Wael Rahman, Choudhury A. IntelliView Technol Inc Calgary AB T2E 2N4 Canada

ISBN: (纸本)9780819494344

In this paper, we proposed a discrete cosine transform (DCT)-based attenuation and accentuation method to remove lighting effects on face images for facilitating face recognition task under varying lighting conditions. In the proposed method, logorithm transform is first used to convert a face image into logarithm domain. Then discrete cosine transform is applied to obtain DCT coefficients. The low-frequency DCT coefficients are attenuated since illumination variations mainly concentrate on the low-frequency band. The high-frequency coefficients are accentuated since when under poor illuminations, the high-frequency features become more important in recognition. The reconstructed log image by inverse DCT of the modified coefficients is used for the final recognition. Experiments are conducted on the Yale B database, the combination of Yale B and Extended Yale B databases and the CMU-PIE database. The proposed method does not require modeling and model fitting steps. It can be directly applied to single face image, without any prior information of 3D shape or light sources.

关键词： Discrete cosine transform (DCT) logarithm transform coefficients attenuation and accentuation illumination pre-processing face recognition

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Software implementation of 2-D grey-level dilation using SKIPSM

Software implementation of 2-D grey-level dilation using SKI...

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conference on machine vision applications, Architectures, and Systems Integration vi

作者： Miller, JWV Waltz, FM ECE Department Univ. of Michigan-Dearborn Dearborn MI 48128-1491 United States Mendota Heights MN 55118-4801 2095 Delaware Avenue United States

ISBN: (纸本)0819426377

The earlier papers on SKIPSM (Separated-Kernel image processing using finite State machines) concentrated mainly on implementations using pipelined hardware. Because of the potential for significant speed increases, the technique has even more to offer for software implementations. However, the gigantic structuring elements (e.g., 51x51 in one pass) readily available in binary morphology using SKIPSM are not practical in grey-level morphology. Nevertheless, useful structuring element sizes can be achieved. This paper describes two such applications: dilation with a 7x7 square and a 7x7 octagon. Previous 2-D SKIPSM implementations had one row machine and one column machine. Two of the implementations described here follow this pattern, but the other has four machines: row, column, and the two 45-degree diagonals. In operation, all of these are one-pass algorithms: The next pixel is ''fetched'' from the input device, the two (or four) machines are updated in turn, and the resulting output pixel is written to the output device. All neighborhood information needed for processing is encoded in the state vectors of the finite-state machines. Therefore, no intermediate image stores are needed. Furthermore, even the input and output image stores can be eliminated if the image processor can keep up with the input pixel rate. Comparisons are provided between these finite-state-machine implementations and conventional implementation of the 2-step and 4-step decompositions, all based on the same structuring elements.

关键词： image processing implementations finite-state machines grey-level morphology

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