疵点

塑料薄膜疵点实时检测系统的设计与实现

Design and Implementation of Real-time Flaw Detecting System for Plastic Membrane

图像形态特征提取在铜箔基板疵点分析中的应用

Shape Character Abstraction Method for the Flaw Analysis of CCL Image

基于二维小波变换和BP神经网络的织物疵点检测方法

Fabric Defect Detection with Two-Dimensional Wavelet Transform and BP Neural Network

基于DSP的薄膜疵点在线检测系统设计与实现

Design and Implementation of DSP Based Pellicle Defect Online Inspection System

基于FPGA的布匹疵点图像实时采集系统

Fabric Flaws ' Realtime Image Grabber System Based on FPGA

基于多线阵CCD的氟塑料薄膜在线疵点检测研究

Research on Fluoride Plastic Film On-line Defect Inspection Based on Multi-linear CCD

基于图像融合的多线阵CCD疵点检测研究

Research on Multi-linear CCD Defect Inspection Based on Image Fusion

基于线阵CCD的织物疵点在线检测系统的研究

Research of an Online Detection System for Fabric Defects based on Line CCD

基于局部熵的CMOS摄像头疵点检测

Defect detection of CMOS camera based on local entropy

疵点分类算法着重考虑布匹疵点特征的选取和BP网络学习算法的优化。

Fabric classification algorithm considers the fabric feature parameters selection and optimization of training algorithm of BP neural network .

感光胶片活性疵点的SEM与EDS分析

The Analysis of Activated Stains Existing on Films by SEM and EDS and IPS

基于DSP的CCD在线检测系统，在纺织面料疵点检测中的应用，是一个崭新的应用课题。

CCD online-detection system based on DSP which applies to defect sense in weave lining is a brand-new applying problem .

用于织物疵点检测的最优Gabor滤波器设计

Design of Optimal Gabor Filters for Textile Defect Detection

Wiener滤波器分解织物图像在织物疵点自动检测中的应用

Application of Wiener Filter to Fabric Defects Automatic Inspection

基于LBP算子和BP神经网络的帘子布疵点识别算法研究

Research about the Cord Fabric Defect recognition Based on the Local Binary Patterns and BP Neural Network

对基于二维Gabor滤波器的检测方法的研究主要是针对隐藏于织物内部的隐性疵点。

The method based on 2-D Gabor filters is researched to detect the invisible deficits .

Canny算子在织物疵点检测中的应用

Application of Canny Operator to Textile Defects Inspection

同时，通过对疵点检测的深入分析以及对前人的研究成果的总结，本文分别提出了基于小波分析的疵点检测算法和基于BP神经网络的疵点分类算法。

Base on the deeply analysis fabric inspection and summarizing the research before , we propose a fabric detection algorithm using wavelet analysis , and an fabric classification algorithm using BP Neural Network .

对于织物疵点的识别分类，本文设计了一个三层BP神经网络，经试验验证对六类织物图像的正确识别率可达95.83%。

For the part of identification of fabric defects , a three layer BP neural network is designed . After testing , six classes fabric image can be correctly identified by the rate of 95.83 % .

在棉纺织厂的使用中，AM接枝淀粉可以全部和大部分取代PVA，并可相应增加纱线的耐磨，消除疵点。

In the cotton mills , the AM grafting starch can all or mostly replace the PVA , and can increase the yarn wearability and eliminate the yarn faults .

本文以纺织面料疵点检测为背景，阐述了研究本课题的意义。构建了基于DSP（Digitalsignalprocessing）的CCD（chargeCoupledDevice）在线检测系统的硬件结构和软件程序。

Grounded on the defect detection of fabric material , this paper tells us the research purport and builds up Hardware and software program of CCD ( Charge Coupled Device ) online-detection based on DSP ( Digital Signal Processing ) .

针对纱线信号在时域上信噪比低，疵点信息难以提取的特点，对K阶矩滤波器和最小熵滤波器两种信号处理方法进行了分析。

The time domain signal of yarn performs low signal to noise ratio and therefore is difficult for defect discrimination . Concerning these problems , two signal processing methods , K-th moment filter and minimum entropy filter are analyzed .

辅助以高性能，低功耗，低成本的ARM7处理器，实现了疵点实时检测算法的硬件平台构建。

Assisted with the high-performance , low-power , low-cost ARM7 processor we implement the construction of the hardware platform of real-time defect detection algorithm .

分别建立了正常纹理匹配和疵点纹理匹配的Gabor滤波器优化设计模型，并采用小生境遗传算法对两种模型进行求解。

Two types of optimization design models of Gabor filters which can match normal texture and defect texture respectively are formulated , and the niche genetic algorithm is employed to solve the models .

借助MATLAB小波分析工具箱，研究了小波分析在对疵点图像进行去噪等图像增强方面的实际应用，并对全局阈值降噪和分层阈值降噪两种方法做了比较。

By means of Wavelet Toolbox in MATLAB , the application of wavelet analysis to image enhancement , especially image de-noising for detecting fabric defects , is studied , and the two kinds of de-noising : global thresholding and level-dependent thresholding are compared .

设计了一套包括用CCD摄像头采集流水线上织物的图像信息，由计算机程序实时处理图像，利用织物疵点自动检测识别算法，对织物疵点进行检测，并进行其他处理。

On the basis of this , we collect fabric image information on flow line using CCD pick-up head , handle image on real time using computer program , utilize fabric defects automatic detection and identification algorithm to detect fabric defects and other processing .

织物疵点智能化判别是用BP神经网络进行的，首先对BP神经网络进行了训练，然后将灰度统计法得到的疵点特征值信息输入到BP神经网络，对疵点进行了分类。

Fabric defects intelligent recognition is done by BP neural network . First BP neural network is being trained , then the basic fabric defect character information , which is acquired by gray level statistical processing , is inputted to BP neural network to classify fabric defects .

用CTT来评定和预测纱线条干不匀及织物的疵点分布具有更高的灵敏度和准确性，对纱线及织物的质量控制更加严格。

Meanwhile , the CTT has the better sensitivity and accuracy when it evaluate the yarn deviation and the fabric fault . So , it control the quality of yarn and fabric more strictly .

几种典型织物疵点的分析表明，基于Wold纹理模型和分形理论的分析方法能准确地检测出织物表面的多种疵点。

After analysing several typical samples , it can be concluded that many fabric defects can be detected with the method combining the Wold - based texture model and fractal theory .

从POY原丝各细分纤维纤度与孔数的对比选择、牵伸温度和网络压空等方面入手，剖析了涤纶牵伸复合丝织物染色疵点的成因及其布面表现形式。

Starting with the comparison of fiber number and hole number of the components , draft temperature and network pressure air , the paper analyses the reasons for the formation of dyeing flaws of the draft compound silk fabrics of polyester fiber and the forms on the cloth .