This issue contains six conference papers; all are indexed separately. Nine additional conference papers appeared in vol. 13, no. 1, under which they are all separately indexed and abstracted. This conference was spec...
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This issue contains six conference papers; all are indexed separately. Nine additional conference papers appeared in vol. 13, no. 1, under which they are all separately indexed and abstracted. This conference was specifically oriented towards those problems in patternrecognition that are specific to the analysis of microscopic cell images. Topics covered include: image analysis, image segmentation, biomedical engineering and imageprocessing.
MACSYM is a hierarchical parallel processing system for pattern understanding applications. It features event-driven parallel processing for knowledge-based understanding of document images. The system is composed of ...
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MACSYM is a hierarchical parallel processing system for pattern understanding applications. It features event-driven parallel processing for knowledge-based understanding of document images. The system is composed of a master processor, slave processors and a large shared memory, and is equipped with versatile communication facilities. The parallel processing software system *** has been developed on MACSYM. It supplies a parallel processing language MacC, an extended version of C, and supports the programming for document image understanding. The Japanese newspaper layout understanding system EXPRESS is being developed on MACSYM. It analyzes a newspaper image and extracts articles in a few seconds.
A survey is made on the control strategies in pattern analysis. Discussions are made on the problems of (1) combinatorial and sequential methods, (2) bottom-up and top-down processes, (3) feedback processes, (4) proce...
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A survey is made on the control strategies in pattern analysis. Discussions are made on the problems of (1) combinatorial and sequential methods, (2) bottom-up and top-down processes, (3) feedback processes, (4) procedural and declarative methods, (5) use of knowledge, and (6) recursive analysis processes. Merits and demerits are pointed out contrastively in and among these methods, with the author"s personal research results. The importance of the declarative method in pattern analysis, especially in the patterns of complex objects, is stressed. The importance of the feedback and recursive applications of analysis algorithms is also mentioned to obtain the accurate results.
This paper describes a knowledge-based weather chart understanding system named WERP, which is working as a picture processing part of our Information understanding System Of BAsic weather Report (ISOBAR). WERP is des...
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This paper describes a knowledge-based weather chart understanding system named WERP, which is working as a picture processing part of our Information understanding System Of BAsic weather Report (ISOBAR). WERP is designed to extract necessary information from a weather chart for generating weather report sentences explaining the chart. This system is based on a structural model of the weather charts. Here, we study what problems are involved in weather chart understanding, how they are solved and how an actual system is organized. Also, picture-processing techniques for weather chart processing and some experimental studies are considered.
This conference contains 51 articles on a variety of subjects related to the fields of imageprocessing and patternrecognition. Among the areas covered are: 2D and 3D image acquisition;static and dynamic imageproces...
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ISBN:
(纸本)0444700684
This conference contains 51 articles on a variety of subjects related to the fields of imageprocessing and patternrecognition. Among the areas covered are: 2D and 3D image acquisition;static and dynamic imageprocessing;object position and orientation;semantic models and image understanding;specialized processing techniques;robotics;computer vision;and objects and characters recognition.
In this paper the state of image database (IDB) systems which have been developed in the past few years is reviewed. We point out the essential problems in IDB design rather than classify the existing or proposed syst...
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In this paper the state of image database (IDB) systems which have been developed in the past few years is reviewed. We point out the essential problems in IDB design rather than classify the existing or proposed systems into an unestablished framework. After giving a general overview, the approaches to IDB and the elements of IDB systems are discussed. Finally, several representative IDB systems are presented.
This issue contains six conference papers;all are indexed separately. Nine additional conference papers appeared in vol. 13, no. 1, under which they are all separately indexed and abstracted. This conference was speci...
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This issue contains six conference papers;all are indexed separately. Nine additional conference papers appeared in vol. 13, no. 1, under which they are all separately indexed and abstracted. This conference was specifically oriented towards those problems in patternrecognition that are specific to the analysis of microscopic cell images. Topics covered include: image analysis, image segmentation, biomedical engineering and imageprocessing.
With suggested computational post-processing workflow for correcting optical distortions, the Fresnel lens can finally be used in lightweight and inexpensive computer vision sensors. Common methods for image enhanceme...
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ISBN:
(纸本)9781509048472
With suggested computational post-processing workflow for correcting optical distortions, the Fresnel lens can finally be used in lightweight and inexpensive computer vision sensors. Common methods for image enhancement do not comprehensively address the blurring artifacts caused by strong chromatic aberrations in images produced by a simple Fresnel optical system. To deliver image quality acceptable for general-purpose color imaging, we propose a computational post-capture processing to enhance the quality of images acquired with a 256-level Fresnel lens. The PSNR quality measure is then applied to estimate resulting quality for different deblurring techniques. A novel technique that removes chromatic blur without computationally expensive deconvolution can be considered a breakthrough as it finally enables in-camera embedded post-processing.
In this paper, we experimentally evaluate the validity of dimension-reduction methods which preserve topology for imagepatternrecognition. imagepatternrecognition uses patternrecognition techniques for the classi...
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ISBN:
(纸本)9783642388866;9783642388859
In this paper, we experimentally evaluate the validity of dimension-reduction methods which preserve topology for imagepatternrecognition. imagepatternrecognition uses patternrecognition techniques for the classification of image data. For the numerical achievement of imagepatternrecognition techniques, images are sampled using an array of pixels. This sampling procedure derives vectors in a higher-dimensional metric space from imagepatterns. For the accurate achievement of patternrecognition techniques, the dimension reduction of data vectors is an essential methodology, since the time and space complexities of data processing depend on the dimension of data. However, the dimension reduction causes information loss of geometrical and topological features of imagepatterns. The desired dimension-reduction method selects an appropriate low-dimensional subspace that preserves the topological information of the classification space.
The task of image segmentation is to group image pixels into visually meaningful objects. It has long been a challenging problem in computer vision and imageprocessing. In this paper we address the segmentation as a ...
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ISBN:
(纸本)9781479921904
The task of image segmentation is to group image pixels into visually meaningful objects. It has long been a challenging problem in computer vision and imageprocessing. In this paper we address the segmentation as a superpixel grouping problem. We propose a novel graph-based segmentation framework which is able to integrate different cues from bilayer superpixels simultaneously. The key idea is that segmentation is formulated as grouping a subset of superpixels that partitions a bilayer graph over superpixels, with graph edges encoding superpixel similarity. We first construct a bipartite graph incorporating superpixel cue and long-range cue. Furthermore, mid-range cue is also incorporated in a hybrid graph model. Segmentation is solved by spectral clustering. Our approach is fully automatic, bottom-up, and unsupervised. We evaluate our proposed framework by comparing it to other generic segmentation approaches on the state-of-the-art benchmark database.
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