The edge feature extraction of images has always been one of the most important and the most basic research tasks in the field of computer vision.
图像的边缘特征提取一直是计算机视觉领域里最重要的和最基本的研究任务之一。
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。
According to features of edge gradient maps of face images, a new eye feature extraction algorithm based on gradient vector flow field was proposed.
根据人脸图像的边缘梯度图提出了一种新的基于梯度向量流场的眼睛特征提取方法。
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。
According to the feature of ear and its position on the side face a method based on edge-tracking was adopted for human ear localization and extraction from side face images.
根据外耳及其所在位置的特征，提出了一种从侧脸图像上准确定位并提取出人耳的新方法。
This paper introduced a MRF (Markov Random Field) -based method of integrating color and spatial edge information to address the problem of lip feature extraction.
讨论了基于马尔可夫随机场(MRF)模型的融合颜色和边缘信息的嘴唇特征提取方法。
We do some researches on the algorithm of CBIR, and pay more attention on the global feature (including color, edge and texture feature) extraction and matching algorithms.
对基于内容的图象信息检索算法作了研究。重点阐述了对颜色、边缘、纹理等全局特征的提取与匹配算法。
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。
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。
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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