Generally speaking, through the binarization of gray-scale images, useful information for the segmentation of touching or overlapping characters may be lost. If we analyze gray-scale images, however, specific topograp...
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In this paper, we present the framework design of IDAP (Intelligent Document Assistant Processor) with the capability of intelligent user interface for pen-based computer systems. No conventional computer user interfa...
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This paper proposes a recognition system of constrained handwritten Hangul (Korean characters) and alphanumeric characters using discrete hidden Markov models (HMM). HMM process encodes the distortion and similarity a...
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In this paper we introduce two technique that can be used together to improve video coding performance. Firstly, block matching motion estimation with spatial transformation (BMST) is used to increase motion compressi...
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In this paper we introduce two technique that can be used together to improve video coding performance. Firstly, block matching motion estimation with spatial transformation (BMST) is used to increase motion compression efficiency, and then motion compensated prediction (MCP) errors are encoded using a hybrid Fractal/DCT scheme. MCP error blocks are classified according to their energy content and they should be coded with a low bit rate. Many of them can be DCT coded, but for those which require a large bit rate to achieve a certain quality, Fractal coding can be efficiency used considering the bit rate constraint. This hybrid scheme speeds up the decoding process, reduces the bit rate, and due the efficiency of motion compensation only a few MCP error images are coded.
To date, there appears to be no total practical solution to the problem of texture discrimination. Thus, grey level histogram correlation often works well, particularly for stochastic texture fields, but this method i...
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To date, there appears to be no total practical solution to the problem of texture discrimination. Thus, grey level histogram correlation often works well, particularly for stochastic texture fields, but this method is less able to distinguish regions within structured texture fields. In this work, the basis for a scheme is presented in which the histograms of local texture properties (grey level differences, including directionality) within windowed regions are correlated with the output from a sample window. We use the output of a novel texture discriminator based on encoded comparisons between adjacent pixels in a 2 × 2 neighbourhood. Results with test images, including those from the Brodatz album, suggest that our feature statistics operator would form the basis of a useful discrimination tool for structural textures in an adaptive system.
Distortions resulting from typical source coding and channel interference are analyzed for monochrome still pictures and evaluated based on a segmentation-based error metric (SEM). The error picture is segmented into ...
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Distortions resulting from typical source coding and channel interference are analyzed for monochrome still pictures and evaluated based on a segmentation-based error metric (SEM). The error picture is segmented into errors at own edges, errors representing exotic or spurious edges, and errors in flat regions to describe edge errors like blurring, exotic structures like blocking and contouring, and residual errors like random noise, respectively. Error parameters or distortion factors are derived by appropriate summation over the segmented components and combined to build the SEM using the impairment addition law by the British Post Office. For a picture data base consisting of typical coding distortions, this leads to a more satisfactory result than a generalized linear summation. Observers are found to be more sensitive to small visible exotic/spurious edges, but less sensitive to edge errors. Yet, large edge errors may rapidly deteriorate the picture quality.
This paper presents a machine vision system for the detection of patch-like defects on apples. The system consists of three parts: initial segmentation, stalk and calyx identification and refinement of defect segmenta...
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This paper presents a machine vision system for the detection of patch-like defects on apples. The system consists of three parts: initial segmentation, stalk and calyx identification and refinement of defect segmentation. Dark patches which may include both defects and stalks/calyxes are first segmented out with a flooding algorithm. To identify stalks and calyxes so as to distinguish them from defects, a structured light and neural network approach is adopted. The structured light provides qualitative 3D shape information, and with the information and the features extracted from apple grey-level images, the neural network classifies each segmented patch as defective or non-defective. For defective ones, the segmentation is refined by a snake algorithm, which improves the accuracy of boundary localization. The experimental results with sample apples show that the proposed system can accurately detect patch-like defects and distinguish them from stalks and calyxes.
In this paper, we present a grammar-based approach to the modeling and recognition of temporal sequences. Unlike hidden Markov models which require humans to determine in advance the appropriate model architecture to ...
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Establishing the identity of a signature by automatic search through a database of signatures is of interest in several areas. This paper describes a system for this purpose. The proposed identification system uses a ...
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This paperpresents a new method for clustering the words in a dictionary into word groups, which are upplied in a Chinese character recognition system with a language model to describe the contextual information. The ...
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