Inspection System for Original Value of Material Decay Based on Image Search Technology

The original value monitoring for material decay is to make use of the video frequency technique, the computer image processing technique and mode identification technique for examination, processing and management of decay image of the material external appearance. In this paper the color characteristic and the veins characteristic of material decay are analyzed and the method and technique to withdraw the characteristic of material decays and to match the image contents are given; thus the search of the material corrosion imagechara cteristic information is realized.     

Inspection System of Material Decay Based on Image Retrieval Technology

Monitoring the material decay make use of the technique of video, computer image processing and pattern identify to detect, process and manage the external material decay image. The color character of the external material decay image are analyzed. The statistics character of the material decay image is pick-up by color histogram, color coherence vector and color correlogram. The comparability of the material decay image is presented by Euclidean distance of the color character. The match and query system of material decay based on image retrieval technology is implemented.     

Video Signals of a Self Scanned Photodiode Array Image Sensor

When self-scanned photodiode array image sensors are applied in object measurements, the outer sizes of the object are included in the video signal of image sensors. The identification and measurement of the object ,and the enhancement of the performance is depended on the symbol extraction of the video output signals. Based on the working principles of self-scanned photodiode array image sensors, the mathematical models of image sensor's video signals are established when the moving object is captured. The comparative method and the measurement error are researched. The results of this paper provide a theoretic basis for the research of video signals processing.     

基于最小阈值法的棉花幼苗识别研究

 面对纯机械式分苗机构经常出现的漏分和多分的问题,本文提出使用基于最小阈值法的图像识别技术对棉花幼苗进行识别和分离。使用了HSV颜色空间内与光照条件无关的H值将RGB真彩色图像转化为灰度图像,以提高图像处理的实时性。基于最小值阈值法,提出一种能够有效地将处于复杂背景下的棉花幼苗茎部图像提取的方法,使用棉花幼苗茎部图像的面积和长宽比等几何信息能有效识别棉花幼苗,并得到棉花幼苗茎部的重心坐标。本文的研究证明了用图像处理中的最小阈值法识别棉花幼苗是可行的。     

Image Format Conversion Between Static DICOM Medical Images and General Medical Images

To make DICOM devices and non-DICOM devices compatible, we need to convert the file format from one to the other. The characteristics of DICOM image file format and normal image file format are studied. The two kinds of file information are construcated, and the file format conversion is implemented. The authors develop a software to convert the file formats between DICOM files and Non-DICOM files. It has been successfully used in PACS, which are operating at hospitals, such as Hospital of anhui province. It is shown that the file format conversion can be implements and can not lose information, and can meet the basic need.     

Fusion method for infrared and visible light images based on image segmentation and stationary wavelet transform

A novel image fusion method based on image segmentation and stationary wavelet transform (SWT) is proposed to improve the visual effect of fused infrared and visible light images. Infrared image is firstly separated into object and background region utilizing Otsu combined with edge detection. Then a multiresolution decomposition using SWT is made to the background region of the infrared image and the visible light image. Neighborhood spatial frequency and absolute value are adopted as fusion rules in low-frequency and high-frequency coefficients. The background fused image is reconstructed by inverse SWT. The final infrared and visible light fused image is obtained by fusing the background fused image and the object region of infrared image base on weighted fusion rule. The experimental results show that the object information of the infrared image is obviously highlighted and the scene information of the visible light image is well represented. The visual effect of fused image is improved efficiently by utilizing the proposed method. The proposed method works better than the traditional Laplacian Pyramid and wavelet transform fusion algorithms in terms of standard deviation, comentropy and mutual information. Experimental results verify its effectiveness.     

机器学习在农作物品种识别中的应用研究进展

机器学习在图像识别领域的成功应用,为农作物品种的自动识别提供了一种新的思路。为了全面了解机器学习在农作物品种识别中的应用现状,把握农作物品种识别的发展趋势和研究方向,本文归纳了农作物图像的常用获取方法,分析了光谱图像和RGB图像结合机器学习方法识别农作物品种的研究现状。基于RGB图像进行农作物品种识别研究起步较早,图像获取成本较低,识别率一般;基于高光谱图像进行农作物品种识别研究近年来发展迅速,识别精度较高,但图像获取成本较高,且易受环境因素影响。通过总结,指出了农作物品种识别研究中存在的问题,认为深度学习在农作物品种自动识别上具有广泛的应用前景     

Image Reconstruction from Imcomplect Data by a Maximum Entropy Reprojecting Technique

In this paper,a new image reconstruction algorithm named maximum entropy reprojecting is developed for missing projection data from some objects are opaque for parts of ray.The results of comparing simulation experiments on the general computer indicate that the quality of reconstructed images by the new algorithm are much better than the tradional maximum entropy algorithm.So the algorithm has reliable propect in application.     

Ultrasound B-mode image enhancement basedon improved histogram equalization

Abstract:The ultrasound B-mode image and the image enhancement are introcued. The cause of amalgamation for histogram equalization, logarithm and order histogram equalization is analyzed theoretically. An improved histogram equalization method is proposed to maintain the gray level. The experimental results with dummy ultrasound B-mode images demonstrate that the image enhancement performance of the proposed method is better than those of histogram equalization, logarithm and order histogram equalization.     

图像识别技术在树木年轮分析中的应用进展

图像识别技术在树木年轮学研究中具有重要的地位和实用价值。在了解树轮图像分析技术发展历程的基础上,介绍了图像处理新技术在树木年轮分析中的应用,综述了国内外的研究进展。从研究区域、思路与方法、应用领域等方面详细综述了国内最新的研究进展。概述了研究存在的问题及未来的展望。结论表明,图像识别技术能够取代树轮实验分析中常规的人工操作,可以大幅度提高实验分析的自动化程度、量测的精准度以及工作效率。虽然图像识别技术在树木年轮实验分析中仍处在起步阶段,但是其超强的技术优势和发展前景已经显现。     

Practical Method of High-Speed Access for Medical Digital Image Sequences

The high-speed access for medical digital image sequences was restricted to special device and complicated system in the past. The authors present a new method of high-speed access for medical digital image sequences which can be performed on general computer by means of the combination of Serial ATA(SATA) and Redundant Array of Independent Disk(RAID).Then they introduce the scheme of system configuration and software program. Lastly the testing result is given and the speediness,cheapness and conveniency of this method are elucidated.     

Automatic quality assessment of fingerprint image

Based on multiple influencing factors, a new method of automatic fingerprint image quality evaluation is proposed for improving the success rate of automation fingerprint identification system (AFIS). At first, the original image’s local texture, global texture, available size and dry or wet condition are regarded as quality impact factors, local texture quality score is calculated by local gradient correlation, and then the last three factors’ quality scores are obtained by block computation thought. Then, with different influence weights, the above four impact factors are linked together to assess image quality synthetically. Finally, effect of partial impact factor is adjusted to correct the final quality score. FVC2004DB2_B is used for algorithm testing. The results suggest that this method can reasonably classify fingerprint image into 5 grades and the precision can achieve 97.5%, and that shows the method is helpful to success rate of AFIS.     

The switching median filter denoising algorithm for encrypted images

Sometimes it is necessary to send the image data to the third party device to process. To ensure the image safety, it is necessary to encrypt the image before processing. A new algorithm for encrypted image processing is proposed. The image owner encrypts     

A contour extraction algorithm for digital images based on water balloons snake model

Due to weak edges and low contrast areas in digital images, such as a left ventricle in Magnetic Resonance Imaging (MRI) images, a deformation curve may leak from the outer boundary when images are segmented using the traditional snake model. An improved algorithm based on the water balloons snake model is introduced to solve this problem. Firstly, the barycenter and the boundary shape area of the left ventricle in a digital MRI image are obtained through mathematical morphology. The left ventricular watershed line is obtained next using a watershed transform algorithm, which is taken as the initial deformation curve in a balloon snake model to capture the contour. Different snake models are tested to digitally tagged MRI images of left ventricles of small pigs. Contrast results indicate that the water balloons snake model can solve the leakage problem in traditional snake and balloon snake models. In addition, the processing speed is improved significantly.     

GF-1和MODIS影像冬小麦长势监测指标NDVI的对比

作物长势是农情遥感监测的重要内容之一。长期以来, 作物长势遥感监测主要基于卫星影像反演的相关植被参数, 如归一化植被指数(NDVI, normalized difference vegetation index)、叶面积指数(LAI, leaf area index)等。本文通过对比研究16 m分辨率GF-1卫星影像及250 m分辨率MODIS影像的NDVI与冬小麦综合茎数、株高、叶绿素浓度之间的关系, 尝试建立遥感监测作物长势指标与地面实测作物长势指标的定量关系。研究发现GF-1 的NDVI与冬小麦综合茎数的相关性最高(R ²=0.8961), 而与其他指标相关性较弱; MODIS的 NDVI指数与冬小麦综合茎数相关性较低(R ²=0.4432), 对作物长势的遥感监测精度较低。统计MODIS冬小麦像元内GF-1像元的NDVI平均值, 并与MODIS的NDVI对比, 发现两者之间的相关性较低(R ²=0.3944); 在消除MODIS与GF-1影像传感器光谱响应函数差异及NDVI尺度效应后, MODIS影像的冬小麦作物长势遥感监测精度得到一定提高(R ²=0.4633)。对MODIS像元内GF-1 NDVI标准差排序发现, MODIS像元内冬小麦长势一致性越高, MODIS的长势遥感监测精度越高。GF-1和MODIS影像NDVI长势监测主要代表地面冬小麦综合茎数, 且卫星影像分辨率越高, NDVI值越能反映实际的作物长势。MODIS像元内冬小麦长势一致性越高, 基于NDVI的MODIS与GF-1数据冬小麦长势监测结果越一致。从区域长势监测角度来看, 尽管MODIS与GF-1数据的监测结果趋势较为一致, 并且通过光谱、尺度归一化能够进一步提高监测结果的一致性, 但MODIS NDVI长势监测总体精度较低, 为满足作物长势精细化监测的业务需要, 应逐步使用高分辨率的遥感数据替代中低分辨率遥感数据进行作物长势遥感监测, 并将其作为长势监测业务化运行的研究重点。     

狼牙山森林公园旅游形象设计研究

旅游形象设计是我国现阶段旅游规划的发展方向和重要内容。本文以河北省狼牙山森林公园为对象,采用适用于各类型旅游地的形象设计技术体系进行全面分析。在此基础上,在CIS理论的基础上重新构建在旅游形象设计框架下对该公园的旅游形象进行了多方案设计,对该公园的合理开发保护有一定的指导意义。     

基于Visual c++矩形标尺智能识别

通过利用图像处理和图像识别领域的边界分割Robert局部边缘检测算子方法及梯度算子区域迭代的阈值图像分割算法相结合来对图像特征进行二次提取,不同于单独采用边界分割与区域分割算法,该算法通过对边缘检测结果的差分结果的迭代分析,有效的增强了识别算法对识别条件的适应性及识别精度,并采用Visual C 编程进行计算机图像辅助设计作为实现手段.     

Image Recognising Based on Support Vector Machine

Support vector machine is the uniform method of statistical learning method,and has become more and more popular in research field.Support vector machine has achieved excellence in pattern recognition and text classification for its high performance in veracity.Support vector machine method was used to process several Binary image and Gray scale image and got a good statistical result.A strategy to select feature vectors has been found out,and the criterion to judge the results are discussed.Compared with other methods,the important conclusion was draw: it performs perfectly in statistic when using support vector machine to detect the image edge.     

A Non-linear Circuit Model of A Self Scanned Photodiode Array Image Sensor

A non-linear circuit model of photodiode built according to the working principle of self-scanned photodiode array image sensor is presented for improving the property of the sensor. Through the analysis of the non_linear circuit model,we get the state equations, and the equations are resolved with Runge_Kutta algorithm. The Runge_Kutta algorithm is realized in C language, and the numeric result of the circuit is obtained. The analysis of the numeric result of the model shows that the non_linear performance of the sensor can be improved by reducing the capcitor of the PN junction and the dynamic performance of the image sensor can be enhanced by paralleling capacitor C M , and all the analysis is consistent with the real measurement results of the sensor. The circuit model of photodiode is improved over previous model.