Description: 基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。-Feature extraction of specified object is an
important preprocessing stage in machine vision
systems. In this paper, we present a novel hybrid
feature extraction method using PCNN (Pulse Coupled
Neural Network) and shape information. First, we use
PCNN firing map train to formulate object’s time
signature, then we use roundness of each firing map to
formulate object’s shape information vector, the final
feature matrix we got is combined time signature and
roundness. We take correlations as our judge criteria
in our experiments. It has been proved that the
algorithm is not sensitivity with the rotation, scaling
and translation of the object and is a useful method for
target recognition applications. Platform: |
Size: 1024 |
Author:wangxiaofei |
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Description: 本文以红外成像制导的图像处理分析和目标识
别为主线，针对各个环节所存在的困难，系统研究了目标识别系统中的图像滤波、
目标分割、二维目标特征提取、三维目标特征提取和分类识别等问题。
-The main line of the image processing and analysis of the infrared imaging guidance and target recognition, target recognition system image filtering system for all aspects of the existing difficulties, object segmentation, two-dimensional target feature extraction, three-dimensional object feature extraction and classification and other issues. Platform: |
Size: 7283712 |
Author:huan |
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Description: ：基于背景建模的运动目标分割是智能视频监控的重要任务，模型的质量直接影响到检测、跟踪、识别等运动分析的准确性．当前的建模方法多是单层的，忽略了像素特征在时域和空域上的联系，模型描述不够准确，对于背景扰动、全局光照变化及复杂的室内外场景等多种情况鲁棒性不强，导致了分割中出现空洞和噪声点．针对这些问题提出了一种双层建模的方法，在第一层提取时域上的像素亮度特征采用码本建模，第二层提取邻域纹理特征采用基于中心对称的局部二值模式建模．实验证明该方法在用于运动分割时，比常用方法具有更好的准确性和鲁棒性．-Moving object segmentation based on background modeling is an important task of intelligent video surveillance, quality models directly affects the detection, tracking, recognition accuracy motion analysis. The current modeling methods are mostly single, ignoring the characteristics of pixels on the temporal and spatial linkages, model description is not accurate enough, the background disturbances, global illumination changes and complex indoor and outdoor scenes and other conditions are not robust strong, leading to a hollow-point division and noise appear. To solve these problems presents a double-modeling method, the pixel brightness feature extraction using time domain modeling codebook in the first layer, the second layer of texture feature extraction using neighborhood center symmetric local binary pattern based construction mode. Experiments show that the method used for motion segmentation when compared with the conventional method has better accuracy and robustness.
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Size: 700416 |
Author: |
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Description: SIFT 特征提取 简单实用 可用于人脸特征分析以及其他物体识别领域-SIFT feature extraction is simple and practical facial feature can be used for analysis, and other areas of object recognition Platform: |
Size: 12288 |
Author:GC |
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Search - Feature Extraction for Object Recognition