• The main contributions of this thesis are as follows:(1) An edge feature detection model based on gradient and phase (GP model) is proposed.

    本文的主要贡献如下:(1)提出了梯度和相位信息相结合的边缘特征检测模型—GP模型。

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  • The fourth chapter discusses in detail a novel method for edge feature detection of images based on wavelet decomposition and reconstruction by means of interval biorthogonal wavelet.

    第四章详细地讨论了利用区间双正交小波,根据小波分解和重构来提取图像的边缘特征的一种新方法。

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  • This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.

    这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。

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  • Regarding this, a novel feature level approach to image fusion is proposed based on discrete dyadic wavelet transform for multi-scale image edge detection.

    本文提出了一种基于离散二进小波变换的多尺度边缘检测和图像融合的方法,实现了特征级图像融合。

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  • As a novel biometric authentication technology, human ear recognition needs to solve the problems of image processing such as edge detection and feature extraction.

    人耳识别作为新的生物特征识别技术,首先要解决作为基础的边缘检测和特征提取等图像处理方面的问题。

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  • A novel shadow edge detection method based on edge feature is presented in this paper firstly.

    该文提出了一种基于边缘特征的阴影边缘检测方法。

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  • The edge is also an important feature of the image and its detection results directly affect the SAR image recognition and analysis.

    而边缘也是图像的重要特征,其检测效果直接影响SAR图像的识别和分析。

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  • One kind of local adaptive smoothing feature enhancement and edge detection algorithm is given.

    提出了一种局域自适应平滑特征增强和边缘提取算法。

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  • The set of edge pixels detected by this algorithm is a useful cue for object's boundary, so it can be taken as an important feature for the human detection system.

    该算法检测到的边缘可以反映物体的轮廓信息,因此可以通过边缘组织高效地检测图像中的人体目标。

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  • Owing to the difficulties in extracting iris edge image, a new iris location algorithm using geometric symmetry feature and edge detection from gray scale image is presented.

    针对虹膜二值边缘图像提取的困难,提出利用虹膜图像的灰度边缘图像以及虹膜的几何特征进行虹膜定位的快速算法。

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  • Image edge detection is the first step to obtain image feature.

    边缘检测是提取图像特征的首要条件。

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  • According to the feature of ear image and requirement of extraction, this paper proposes a new edge detection method based on contour composition.

    本文针对人耳图像的局部特征和识别要求提出一种基于轮廓合成的边缘检测方法。

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  • Experiment shows that the method can much better get the feature of the textile defects and has a much better edge detection result of the textile defects.

    实验证明这种方法能有效地获取织物疵点特征,并得到较为理想的边缘检测效果。

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  • In this paper, we use edge detection, integral projection and template matching to compute the dates of the face feature, and have acquired a higher veracity.

    本文利用边缘检测、积分投影及模板匹配等相结合的方法,比较准确的获得了人脸各个特征部位的数据。

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  • Because the images edge can be affected by noise more easily than the region feature, defect region-detection is proposed by combining mathematics morphology and optimal threshold method.

    鉴于图像边缘特征易受噪声影响,而区域特征受噪声影响要小得多,提出利用数学形态学和最佳阈值分割相结合的方法来实现缺陷区域提取。

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  • Because the images edge can be affected by noise more easily than the region feature, defect region - detection is proposed by combining mathematics morphology and optimal threshold method.

    鉴于图像边缘特征易受噪声影响,而区域特征受噪声影响要小得多,提出利用数学形态学和最佳阈值分割相结合的方法来实现缺陷区域提取。

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  • According to the feature of ear image and requirement of extraction, this paper proposes a new edge detection method based on contour composition.

    采用区域性增强法对人脸图像进行预处理,用基于知识库的方法提取人脸几何特征。

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  • Edge detection is an important feature of the image, it contains the information used to identify the target.

    边缘是图像的重要特征,包含了图像中用于识别目标的信息。

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  • Edge detection is an important feature of the image, it contains the information used to identify the target.

    边缘是图像的重要特征,包含了图像中用于识别目标的信息。

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