The lateral inhibition mechanism of organisms and digital cellular neural network (DCNN) are introduced. Then the integration of them is studied. Referenced some beneficial conclusions of DCNN, the model of digital ac...
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The lateral inhibition mechanism of organisms and digital cellular neural network (DCNN) are introduced. Then the integration of them is studied. Referenced some beneficial conclusions of DCNN, the model of digital acyclic lateral inhibition network (DALIN) is proposed in the paper. Until now most of existing associational memory algorithm only can operate on the two-value state {-1, +1}. Enlightened by these memory algorithms, especially by the DCNN, a new associational memory algorithm is proposed based on the DALIN. The new algorithm can operate on gray image, which includes 256 states, namely from 0 to 255. The implementation condition of the new algorithm is proposed and proved. Then it's applied on a cell's gray image with some noise. The results show that noises in images can be effectively filtered with the new algorithm. The learning effect on input samples is perfect. The calculation quantity of weight values is decreased and the learning time is shortened. images processed by lateral inhibition networks in the domain of space are accorded with the requirement of human beings' vision. The new algorithm is significative for the learning and patternrecognition of images, such as cell recognition and X- ray diagnosis. The DALIN also can be applied in other domain of image process, such as edge extraction and scene matching.
Many patternrecognition problems can be solved by mapping the input data into an n-dimensional feature space in which a vector indicates a set of attributes. One powerful patternrecognition method is the Hough-trans...
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ISBN:
(纸本)9728865406
Many patternrecognition problems can be solved by mapping the input data into an n-dimensional feature space in which a vector indicates a set of attributes. One powerful patternrecognition method is the Hough-transform, which is usually applied to detect specific curves or shapes in digital pictures. In this paper the Hough-transform is applied to the time series data of neurotransmitter vesicle releases of an auditory model. Practical vowel recognition of different speakers with the help of this transform is investigated and the findings are discussed.
In this paper, a method for improvement of image quality using the error diffusion which considers the APL process is proposed. In the proposed method, the APL process is performed before the error diffusion process. ...
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A new technology evaluation of fingerprint verification algorithms has been organized following the approach of the previous FVC2000 and FVC2002 evaluations, with the aim of tracking the quickly evolving state-ofthe- ...
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This paper describes a method for automaticallyassessin g the qualityo f manufactured roof-tiles using digital audio signal processing and patternrecognition techniques. A prototype system has been developed that is ...
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The purpose of this paper is to describe a method developed for estimation of the diameter of circular disks resulting from antibacterial cultures, immersed in a bacterial gel, using digitalimages of the growth recip...
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In this paper, a new adaptive multichannel filter for the detection and removal of impulsive noise, bit errors and outliers in digital color images is provided. The proposed nonlinear filter takes the advantages of th...
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In this paper, a new embedded wavelet packet image coder algorithm is proposed for an effective image coder using correlation between partitioned coefficients. This new algorithm presents parent-child relationship for...
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A method of image zoom-in is presented in the paper based on Bézier surface interpolation. By the method, a piecewise surface in C1 continuity for each color component of a digitalimage is constructed in terms o...
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A method of image zoom-in is presented in the paper based on Bézier surface interpolation. By the method, a piecewise surface in C1 continuity for each color component of a digitalimage is constructed in terms of bicubic Bézier interpolation. Then, the zoom-in operation to the image could be implemented by sampling the surface with various sampling rate. Experimental results show that the method is computationally efficient and the quality of the zoomed-in images could be greatly improved by using the method.
Edge detection is one of the most widely used operations in imageprocessing or computer vision. The reason for this is that edges provide useful information such as outline of an object or boundary between regions. T...
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Edge detection is one of the most widely used operations in imageprocessing or computer vision. The reason for this is that edges provide useful information such as outline of an object or boundary between regions. Those information can be used in a lot of different context, for example, shape or patternrecognition which may be used in computer vision or OCR (Optical Character recognition) system. In general, an edge can be defined as a significant changes or discontinuities in gray level. Any operator that is sensitive to this kind of changes will operate as an edge detector. A pixel having a change that exceeds a specified threshold value can be defined as an edge pixel However, most existing edge detectors need to manually select the threshold(s) and apply it globally throughout the image. Even with the well known Canny edge detector, which applies hysteresis thresholding rather than simply selecting a threshold value to apply everywhere, it still needs to select a high threshold and a low threshold manually. In this paper, we presented a new perceptual thresholding strategy for gradient based local edge detection. This new method calculates the gradient threshold value automatically based on local intensity information, and due to the nature of its local computation, it is very suitable for fast hardware implementation and real time imaging application.
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