In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to ...
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This paper describes a unique cross-phoneme speaker identification experiment, using deliberately mismatched phoneme sets for training and testing. The underlying goal is to identify features that represent broad indi...
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A new method for the reduction of the number of colors in a digital image is proposed. The new method is based on the developed of a new neural network classifier that combines the advantages of the Growing Neural Gas...
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In order to successfully locate and retrieve document images such as technical articles and newspapers, a text localization technique must be employed. The proposed method detects and extracts homogeneous text areas i...
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ISBN:
(纸本)9780889868243
In order to successfully locate and retrieve document images such as technical articles and newspapers, a text localization technique must be employed. The proposed method detects and extracts homogeneous text areas in document images indifferent to font types and size by using connected components analysis to detect blocks of foreground objects. Next, a descriptor that consists of a set of structural features is extracted from the merged blocks and used as input to a trained Support Vector Machines (SVM). Finally, the output of the SVM classifies the block as text or not.
Most of the existing document-binarization techniques deal with many parameters that require a priori setting of their values. Due to the unknown of the ground-truth images, the evaluation of document binarization tec...
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ISBN:
(纸本)9780889867192
Most of the existing document-binarization techniques deal with many parameters that require a priori setting of their values. Due to the unknown of the ground-truth images, the evaluation of document binarization techniques is subjective and employs human observers for the estimation of the appropriate parameter values. The selection of the appropriate values for these parameters is crucial and influences to the final binarization. However, there is no predetermined set of parameters that guarantees optimal binarization for all document images. This paper proposes a new technique that allows the estimation of proper parameters values for each one of the document binarization techniques. The proposed approach is based on a statistical performance analysis of a set of binarization results, which are obtained by applying various binarization techniques with different parameter values. The proposed statistical performance analysis can also depicts the best document binarization result obtained by a set of document binarization techniques.
We propose an adaptive motion compensated frame interpolation scheme which is capable of developing a frame rate from a lower number into a higher number and a decoded video quality at the decoder. The proposed algori...
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This paper presents a frame interpolation algorithm using the motion information of some object within the estimated blocks. The proposed algorithm uses two initial frames that are generated based on the backward and ...
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The problem of defining an appropriate measure of the degree of nonstationarity for stochastic processes that exhibit cyclostationarity is addressed. After discussing several candidate measures of degree of nonstation...
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The problem of defining an appropriate measure of the degree of nonstationarity for stochastic processes that exhibit cyclostationarity is addressed. After discussing several candidate measures of degree of nonstationarity, one particularly promising measure is adopted. By decomposing this measure, several component measures are arrived at. Bounds on these measures are derived and their utility in applications involving signal detection and estimation is established. Examples are presented to illustrate the calculation of degrees of nonstationarity for several types of cyclostationary signals.
Deep learning (DL) has significantly advanced various industries, including semiconductors, by providing sophisticated methods for analyzing emerging device data. Transfer learning (TL), a prominent DL topology, lever...
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Traditionally, signal processing is considered simply lowlevel processing. In the past decade, however, signal processing has grown to become the area where a variety of tools are created to solve high-level problems ...
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