recognition of three dimensional objects independent of size, position and orientation is an important and difficult problem of scene analysis. The use of three dimensional moment invariants is proposed as a solution....
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recognition of three dimensional objects independent of size, position and orientation is an important and difficult problem of scene analysis. The use of three dimensional moment invariants is proposed as a solution. The generalization of the results of two dimensional moment invariants which had linked two dimensional moment invariants to binary quantics is done by linking three dimensional moments to ternary quantics. The existence and number of n**t**h order moments in two and three dimensions is explored. Algebraic invariants of several ternary forms under different orthogonal transformations are derived by using the invariant property of the coefficients of ternary forms. The result is a set of three dimensional moment invariants which are invariant under size, orientation and position change.
Object location in computed tomography images is a preliminary step required for many automated measurements which may be useful in many diagnostic procedures. Most object location, imageprocessing.techniques are eit...
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Object location in computed tomography images is a preliminary step required for many automated measurements which may be useful in many diagnostic procedures. Most object location, imageprocessing.techniques are either globally based such as histogram segmentation or locally based such as edge detection. The method described uses both local and global information for object location. The technique has been applied to the location of suspected tumors in CT lung and brain images. Sorting and merging steps are required for eliminating noise regions but all suspected tumor regions have been located. Measurements such as boundary roughness or density statistics may also be made on the objects and used to further identify suspicious regions for further study by the radiologists.
This paper reviews recent developments in the use of iterative (or ″relaxation″ ) methods in image analysis. Applications of these methods include histogram modification, noise cleaning, edge and curve detection, th...
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This paper reviews recent developments in the use of iterative (or ″relaxation″ ) methods in image analysis. Applications of these methods include histogram modification, noise cleaning, edge and curve detection, thinning, angle detection, template matching, and region labelling. These applications are briefly described, and references are given to papers and reports in which more detailed discussions and examples can be found.
Latent fingerprints are fingerprint impressions unintentionally left on surfaces at a crime scene. They are crucial in crime scene investigations for making identifications or exclusions of suspects. Determining the q...
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ISBN:
(数字)9781538661000
ISBN:
(纸本)9781538661000
Latent fingerprints are fingerprint impressions unintentionally left on surfaces at a crime scene. They are crucial in crime scene investigations for making identifications or exclusions of suspects. Determining the quality of latent fingerprint images is crucial to the effectiveness and reliability of matching algorithms. To alleviate the inconsistency and subjectivity inherent in feature markups by latent fingerprint examiners, automatic processing.of latent fingerprints is imperative. We propose a deep neural network that predicts the quality of image patches extracted from a latent fingerprint and knits them together to predict the quality of a given latent fingerprint. The proposed approach eliminates the need for manual ROI markup and manual feature markup by latent examiners. Experimental results on NIST SD27 show the effectiveness of our technique in latent fingerprint quality prediction.
A system is described that detects object outlines in television images in real-time. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system...
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A system is described that detects object outlines in television images in real-time. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges and represents them as chain codes. image statistics, useful for higher level tasks such as patternrecognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process.
Background subtraction is the first step of many video surveillance applications. What is considered background varies by application, and may include regular, systematic, or complex motions. This paper explores the u...
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Background subtraction is the first step of many video surveillance applications. What is considered background varies by application, and may include regular, systematic, or complex motions. This paper explores the use of several different local spatio-temporal models of a background, defined at each pixel in the image. We present experiments with real image data and conclude that appropriate local representations are sufficient to make background models of complicated real world motions. Empirical studies illustrate, for example, that an optical flow-based model is able to detect emergency vehicles whose motion is different from those typically observed in traffic scenes. We conclude that "different models are appropriate for different scenes", but give criteria by which one can choose which model will be best.
image composition (or mosaicing) has attracted a growing attention in recent years as one of the main elements in video analysis and representation. In this paper we deal with the problem of global alignment and super...
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ISBN:
(纸本)0769521584
image composition (or mosaicing) has attracted a growing attention in recent years as one of the main elements in video analysis and representation. In this paper we deal with the problem of global alignment and super-resolution. We also propose to evaluate the quality of the resulting mosaic by measuring the amount of blurring. Global registration is achieved by combining a graph-based technique that exploits the topological structure of the sequence induced by the spatial overlap - with a bundle adjustment which uses only the homographies computed in the previous steps. Experimental comparison with other techniques shows the effectiveness of our approach.
image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data and are too computationally expensiv...
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ISBN:
(纸本)9781665448994
image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data and are too computationally expensive to run on mobile devices. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based image denoising solution that can demonstrate high efficiency on smartphone GPUs. For this, the participants were provided with a novel large-scale dataset consisting of noisy-clean image pairs captured in the wild. The runtime of all models was evaluated on the Samsung Exynos 2100 chipset with a powerful Mali GPU capable of accelerating floating-point and quantized neural networks. The proposed solutions are fully compatible with any mobile GPU and are capable of processing.480p resolution images under 40-80 ms while achieving high fidelity results. A detailed description of all models developed in the challenge is provided in this paper.
In this paper, we describe an approach to recognizing location from mobile devices using image-based web search. We demonstrate the usefulness of common image search metrics applied on images captured with a camera-eq...
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ISBN:
(纸本)0769521584
In this paper, we describe an approach to recognizing location from mobile devices using image-based web search. We demonstrate the usefulness of common image search metrics applied on images captured with a camera-equipped mobile device to find matching images on the World Wide Web or other general-purpose databases. Searching the entire web can be computationally overwhelming, so we devise a hybrid image-and-keyword searching technique. First, image-search is performed over images and links to their source web pages in a database that indexes only a small fraction of the web. Then, relevant keywords on these web pages are automatically identified and submitted to an existing text-based search engine (e.g. Google) that indexes a much larger portion of the web. Finally, the resulting image set is filtered to retain images close to the original query. It is thus possible to efficiently search hundreds of millions of images that are not only textually related but also visually relevant. We demonstrate our approach on an application allowing users to browse web pages matching the image of a nearby location.
We propose blind segmentation of images into shape-related 'patches' based on pre-calculated local symmetries (Van Tender, G.J. & Ejima, Y. (1999). (Forthcoming a) Flexible computation of shape symmetries....
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We propose blind segmentation of images into shape-related 'patches' based on pre-calculated local symmetries (Van Tender, G.J. & Ejima, Y. (1999). (Forthcoming a) Flexible computation of shape symmetries. Submitted for publication) in shape boundary contours. First, lateral weights between all points in the boundary contour map are assigned analogous to Euclidean distance maps in watershed segmentation (Beucher, S. & Lantejoul, C. (1979). Use of watersheds in contour detection. proceedings of the International Workshop on imageprocessing. CCETT, Rennes, France.). Lateral weights are then used to: (1) extract local maxima in symmetries;(2) link maxima within locally enclosed boundary contours;and (3) reconstruct shape contours using symmetry maxima as 'seeds'. The new model overcomes weaknesses of watershed segmentation. The new model closes gaps in relatively more solid image contours, but it is fundamentally different from methods based on contour interpolation (Grossberg, S., Mingolla, E. & Todorove, D. (1989). A neural network architecture for preattentive vision, ieee Transactions on Biomedical Engineering 36, 65-84;Heitger, F. & von der Heydt, R. (1993). A computational model of neural contour processing. figure-ground segregation and illusory contours. proceedings of the Fourth International conference on computer Vision, ieeecomputersociety Press, Washington D.C. (pp. 32-40)). images are segmented into shape-relevant color-by-number-like patches which compare well to related methods (Gauch, J. & Pizer, M. (1993). The intensity axis of symmetry and its application to image segmentation, ieee Transactions on pattern Analysis and Machine Intelligence, 15 (8), 753-770;Ilg, W. & Ogniewicz, R. (1995). The application of Voronoi skeletons to perceptual grouping in line images, proceedings of the 11th International conference on patternrecognition, The Hague, The Netherlands, pp. 382-385;Zhu, S.C. & Yuille, A.L. (1996) FORMS: a flexible object recognition and mo
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