In this paper, we study the calculation for the fracture area of the composite material specimens using digital image processing techniques. This study was able to calculate the area of the fracture region through the main operation step 7 on the basis of improved image. To extract the area in the original image, we have to use opening operation, close operation, the Hit-or-Miss operation and Bottom hat filter, Top hat filter, etc. In particular, to extract the area of the composite specimen discussed in this study, we have to use the combination of the operations and filters because it is non-isotropic material, or should develop a new algorithm based on it.

In this paper, we study the calculation for the fracture area of the tension specimens using digital image processing techniques. This study was able to calculate the area of the fracture region on the basis of improved image. To extract the area in the original image, we have to use opening operation, close operation, the Hit-or-Miss operation and Bottom hat filter, Top hat filter, etc. In particular, to extract the area of the composite specimen discussed in this study, we have to use the combination of the operations and filters because it is non-isotropic material, or should develop a new algorithm based on it.

해충의 발생시기와 발생량에 대한 정확한 예찰정보는 해충의 효율적인 종합적 방제를 위하여 필수적으로 요구된다. 해충의 효율적인 발생 예찰조사를 위해 디지털 영상처리 알고리즘을 이용하여 벼농경지에서 주요 해충인 멸구류를 자동적으로 인식하고 밀도를 측정하도록 하였다. 야외경작지에서 촬영한 입력영상에 대해 구성인자분해과정, 탑헷(top-hat)변환, 역치적용, 최소/최대 필터링 등의 방법을 적용하여 벼 잎에 붙어 있는 멸구 개체를 인식하고 개체수를 헤아렸다. 평균인식율은 95.8%를 보였다. 또한 인지된 각 멸구류 개체 크기를 측정하여 멸구류의 연령분포 추정을 가능하게 하였다

Radar image data were collected through the on-line data acquisition system of A/D converter and personal computer, and the image was restorated on CRT or plotter after digital image processing of the data. The digital image processing system which was developed for this study, consisted of some kinds of software as follows : rearrangement, transformation, and enhancement of the image data in real space or frequency space by Fourier transform, edge detection of the image, compact processing, state inferential processing, and so on. Since the image of PPI radar sweeps from the center to the circumference of a circle, the image within a given period has the shape of fan. Therefore the acquired data were transformed to have the same interval as that of data in outmost concentricity. The results of various image processing methods using transformed data were better than those of the methods using original data.