电脑知识与技术
電腦知識與技術
전뇌지식여기술
Computer Knowledge and Technology
2015年
5期
190-192
,共3页
沙粒%智能检测%图像分割%形态特征
沙粒%智能檢測%圖像分割%形態特徵
사립%지능검측%도상분할%형태특정
sand grains%intelligent detection%image segmentation%morphology of sand
沙粒粒径的测定和统计可以用来评价沙丘转移和沙漠气候的变化状况。为实现沙粒粒径的非接触测量,在实验室使用单反相机、直尺和计算机等设备,构建沙粒粒形参数的检测环境。以野外采集的沙粒为研究对象,利用matlab图像处理工具箱对沙粒图像锐化轮廓、图像降噪、粘连沙粒分割、特征提取和计数。通过将图像处理得到的沙粒等效粒径与Rise-2008系列激光粒径分析仪得到的检测结果比较发现:二者的粒径检测结果误差保持在较小范围,无显著差异。进而对沙粒长径、短径、圆形度、粒形参数检测和统计,并且在图像中对沙粒质心位置进行标定,基本实现了对于沙粒主要形态特征的检测。实验表明,该方法为快速检测沙粒形态特征提供了有效手段。这种方法稳定性好、检测精度较高、成本低,而且省时省力。
沙粒粒徑的測定和統計可以用來評價沙丘轉移和沙漠氣候的變化狀況。為實現沙粒粒徑的非接觸測量,在實驗室使用單反相機、直呎和計算機等設備,構建沙粒粒形參數的檢測環境。以野外採集的沙粒為研究對象,利用matlab圖像處理工具箱對沙粒圖像銳化輪廓、圖像降譟、粘連沙粒分割、特徵提取和計數。通過將圖像處理得到的沙粒等效粒徑與Rise-2008繫列激光粒徑分析儀得到的檢測結果比較髮現:二者的粒徑檢測結果誤差保持在較小範圍,無顯著差異。進而對沙粒長徑、短徑、圓形度、粒形參數檢測和統計,併且在圖像中對沙粒質心位置進行標定,基本實現瞭對于沙粒主要形態特徵的檢測。實驗錶明,該方法為快速檢測沙粒形態特徵提供瞭有效手段。這種方法穩定性好、檢測精度較高、成本低,而且省時省力。
사립립경적측정화통계가이용래평개사구전이화사막기후적변화상황。위실현사립립경적비접촉측량,재실험실사용단반상궤、직척화계산궤등설비,구건사립립형삼수적검측배경。이야외채집적사립위연구대상,이용matlab도상처리공구상대사립도상예화륜곽、도상강조、점련사립분할、특정제취화계수。통과장도상처리득도적사립등효립경여Rise-2008계렬격광립경분석의득도적검측결과비교발현:이자적립경검측결과오차보지재교소범위,무현저차이。진이대사립장경、단경、원형도、립형삼수검측화통계,병차재도상중대사립질심위치진행표정,기본실현료대우사립주요형태특정적검측。실험표명,해방법위쾌속검측사립형태특정제공료유효수단。저충방법은정성호、검측정도교고、성본저,이차성시성력。
The mensuration and statistics of sand can be used to evaluate sand dune and desert climate change. In order to realize the non-contact measurement of the sand size, a sand grain shape parameters testing environment is created with digital camera, ruler and computer in the laboratory. Then taking the sand grains in the field as the research object, making the outline sharpening, image denoising, extracting the adhesion of sand grains and count them with MATLAB image processing toolbox. By compare the measured results with the Rise-2008 laser particle size analyzer. The results show that the error between the two methods is small, and the results of the two methods are not significantly different. Then statistic sand grain size, short diameter, roundness and parti?cle size, also the position of sand particles in the image is calibrated. This method realize the detection of main morphological char?acters of the grains. Experimental results show that this method can provide an effective method to detect the morphological charac?teristics of sand grains. This technique is good stability, high detection accuracy, low detection cost, also save time and effort.