We present an overview of DNA microarray image requirements for automated processing.and information extraction from spotted glass slides. Motivation of our review comes from the need to automate high-throughput micro...
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We present an overview of DNA microarray image requirements for automated processing.and information extraction from spotted glass slides. Motivation of our review comes from the need to automate high-throughput microarray data processing.due to exponentially growing amounts of microarray data. In order to automate microarray imageprocessing.and draw biologically meaningful conclusions from experiments, one has to understand the processing.flow, modeling assumptions, uncertainties involved, and the computational tradeoffs of multiple approaches. We present a model of an ideal microarray image and microarray deviations from the model in real experiments. In the summary, we discuss several open problems and the current challenges of high-throughput microarray imageprocessing.
We present a proof of concept system to represent and reason about hockey play. The system takes as input player motion trajectory data tracked from game video and supported by knowledge of hockey strategy, game situa...
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This paper proposes a method of six-color separation using additional colorants with less dot visibility to reduce the color difference and graininess. In conventional six-color separation, the use of light magenta an...
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This paper proposes a method of six-color separation using additional colorants with less dot visibility to reduce the color difference and graininess. In conventional six-color separation, the use of light magenta and light cyan is generally an effective way of reducing the visibility of dots in bi-level printing devices, i.e., light magenta and light cyan are used in a bright region instead of magenta and cyan. However, the hue values for light magenta and light cyan differ from those for magenta and cyan in CIELAB space, making the colorimetric reproduction less inaccurate. Therefore, to minimize this inaccuracy, the proposed method uses yellow and light magenta colorants as additional colorants. In a bright region, magenta is replaced with light magenta and yellow, while cyan is replaced with light cyan and light magenta. These combinations reduce the hue difference, as they create colors with a similar hue to magenta and cyan. In addition, a smooth image can be simultaneously obtained due to the lower dot visibility of the additional colorants. In a middle region, magenta is replaced with light magenta and magenta, while cyan is replaced with light cyan and cyan. Since the use of these two colorants with different concentrations makes a coarse dot pattern, this phenomenon is reflected based on a quantitative granularity metric. Finally, in a dark region, only the magenta and cyan colorants are used as usual. Experiments show that the proposed method can simultaneously produce a colorimetric and smooth-tone reproduction.
The restoration of images is an important and widely studied problem in computer vision and imageprocessing. Various image filtering strategies have been effective, but invariably make strong assumptions about the pr...
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The restoration of images is an important and widely studied problem in computer vision and imageprocessing. Various image filtering strategies have been effective, but invariably make strong assumptions about the properties of the signal and/or degradation. Therefore, these methods typically lack the generality to be easily applied to new applications or diverse image collections. This paper describes a novel unsupervised, information-theoretic, adaptive filter (UINTA) that improves the predictability of pixel intensities from their neighborhoods by decreasing the joint entropy between them. Thus UINTA automatically discovers the statistical properties of the signal and can thereby restore a wide spectrum of images and applications. This paper describes the formulation required to minimize the joint entropy measure, presents several important practical considerations in estimating image-region statistics, and then presents results on both real and synthetic data.
This paper describes a system for pedestrian detection in stereo infrared images. The system is based on three different underlying approaches: warm area detection, edgebased detection, and v-disparity computation. St...
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This paper describes a system for pedestrian detection in stereo infrared images. The system is based on three different underlying approaches: warm area detection, edgebased detection, and v-disparity computation. Stereo is also used for computing the distance and size of detected objects. A final validation process is performed using head morphological and thermal characteristics. Neither temporal correlation, nor motion cues are used in this processing. The developed system has been implemented on an experimental vehicle equipped with two infrared camera and preliminarily tested in different situations.
Real-time object detection is essential for many computer vision applications. Many rapid detection algorithms are based on using cascades of tests. But existing design criteria for cascades either ignore the time com...
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Real-time object detection is essential for many computer vision applications. Many rapid detection algorithms are based on using cascades of tests. But existing design criteria for cascades either ignore the time complexity of the tests or make over-simplified assumptions about them. This paper gives a criterion for designing a time-efficient cascade that explicitly takes into account the time complexity of tests (as evaluated by computer run time) including the time for pre-processing. We design a greedy algorithm to minimize this criterion (noting that the full problem is NP-complete). Finally, we illustrate our method on the task of text detection in city scenes. This gives a text detection algorithm that runs at 0.025 seconds per 320×240 image, which is equivalent to 40 frames per second. This is a speed up factor of 2.5 compared to our previous text detector. It gives a realtime system which can be used for applications to help the blind and visually impaired.
This paper introduces a formulation which allows using wavelet-based priors for image segmentation. This formulation can be used in supervised, unsupervised, or semi-supervised modes, and with any probabilistic observ...
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This paper introduces a formulation which allows using wavelet-based priors for image segmentation. This formulation can be used in supervised, unsupervised, or semi-supervised modes, and with any probabilistic observation model (intensity, multispectral, texture). Our main goal is to exploit the well-known ability of wavelet-based priors to model piece-wise smoothness (which underlies state-of-the-art methods for denoising, coding, and restoration) and the availability of fast algorithms for wavelet-based processing. The main obstacle to using wavelet-based priors for segmentation is that they're aimed at representing real values, rather than discrete labels, as needed for segmentation. This difficulty is sidestepped by the introduction of real-valued hidden fields, to which the labels are probabilistically related. These hidden fields, being unconstrained and real-valued, can be given any type of spatial prior, such as one based on wavelets. Under this model, Bayesian MAP segmentation is carried out by a (generalized) EM algorithm. Experiments on synthetic and real data testify for the adequacy of the approach.
The problem of deciding whether two pixels in an image have the same real world color is a fundamental problem in computer vision. Many color spaces are used in different applications for discriminating color from int...
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ISBN:
(纸本)0769521584
The problem of deciding whether two pixels in an image have the same real world color is a fundamental problem in computer vision. Many color spaces are used in different applications for discriminating color from intensity to create an informative representation of color The major drawback of all of these representations is that they assume no color distortion. In practice the colors of real world images are distorted both in the scene itself and in the image capturing process. In this work we introduce Color Lines, an image specific color representation that is robust to color distortion and provides a compact and useful representation of the colors in a scene.
This paper presents a novel representation for dynamic scenes composed of multiple rigid objects that may undergo different motions and be observed by a moving camera. Multi-view constraints associated with groups of ...
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ISBN:
(纸本)0769521584
This paper presents a novel representation for dynamic scenes composed of multiple rigid objects that may undergo different motions and be observed by a moving camera. Multi-view constraints associated with groups of affine-invariant scene patches and a normalized description of their appearance are used to segment a scene into its rigid parts, construct three-dimensional projective, affine, and Euclidean models of these parts, and match instances of models recovered from different image sequences. The proposed approach has been implemented, and it is applied to the detection and recognition of moving objects in video sequences and the identification of shots that depict the same scene in a video clip (shot matching).
A new and fast way to find local image correspondences for wide baseline image matching is described. The targeted application is visual navigation, e.g. of a semi-automatic wheelchair. Such applications pose some add...
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ISBN:
(纸本)0769521584
A new and fast way to find local image correspondences for wide baseline image matching is described. The targeted application is visual navigation, e.g. of a semi-automatic wheelchair. Such applications pose some additional requirements, like the need to work with natural landmarks rather than artificial markers, and the need to recognize locations fast. The restricted motion of the camera can be exploited to simplify the feature extraction. These features should support their identification from different, but nevertheless restricted viewing directions, and under variable illumination conditions. The paper proposes a specialization of so-called affine invariant regions for these particular conditions, which in this case simplifies to column segments. Their applicability is wider than robot navigation, and includes localization for wearable computing and scene recognition for automatic movie indexing.
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