processing of real-time X-ray images of randomly-oriented and touching pistachio nuts for product inspection is considered. We describe the imageprocessing used to isolate individual nuts (segmentation). This involve...
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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 imageprocessing 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.
A high throughput is often required in many machinevision systems, especially on the assembly line in the semiconductor industry. To develop a non-contact three-dimensional dense surface reconstruction system for rea...
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ISBN:
(纸本)9780819494344
A high throughput is often required in many machinevision 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.
There are two crucial, complementary, issues faced during design and implementation of practically any but a simple imageprocessing library. First is an ability to represent a variety of image types, typically the di...
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ISBN:
(纸本)0819426377
There are two crucial, complementary, issues faced during design and implementation of practically any but a simple imageprocessing 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 imageprocessing 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.
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 ve...
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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.
A novel computational geometry architecture for imageprocessing and display applications is described, based upon the logarithmic conformal mapping of a pixel space. Parallel algorithms for image rotation, scaling an...
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A novel computational geometry architecture for imageprocessing 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.
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 ...
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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.
The registration of images is a fundamental task in numerous applications in medical imageprocessing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure...
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ISBN:
(纸本)9781467361842
The registration of images is a fundamental task in numerous applications in medical imageprocessing. 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.
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 ...
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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 machinevision 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.
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...
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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.
The earlier papers on SKIPSM (Separated-Kernel imageprocessing using finite State machines) concentrated mainly on implementations using pipelined hardware. Because of the potential for significant speed increases, t...
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ISBN:
(纸本)0819426377
The earlier papers on SKIPSM (Separated-Kernel imageprocessing 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.
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