우리나라는 여러 건의 여객선 사고를 겪으면서, 여객선 안전관리를 위해 다양한 제도를 운영하고 있다. 2021년 기준 우리나라 연안을 운항하는 여객선 162척 중, 차량갑판이 개방된 형태의 차도선이 105척(65 %)을 차지하고 있다. 차도선은 2～4개의 섬을 경유하는 운항 패턴을 가지고 있다. 출항지(모항)에서 안전점검은 선원과 운항관리실의 운항감독관, 해사안전감독관에 의해 실시된다. 경유지에서 의 안전점검은 자체점검이 실시되는 경우가 있다. 여느 제도와 마찬가지로 제도적, 현실적 한계 등이 있다. 이를 위해 영상처리기법을 활 용하여 차량을 검출하고 이를 선박 복원성 계산과 연동하는 방안을 제안하고자 본 연구를 수행하였다. 차량 검출을 위해 차영상을 이용 하는 방법과 기계학습을 이용하는 방법을 사용하였다. 검출된 데이터를 선박 복원성 계산에 활용하였다. 기계학습을 통해 차량을 검출하 는 경우, 차영상에 의한 차량 검출 방법보다 차량 식별에 안정적임을 알 수 있었다. 다만, 카메라가 일몰과 같은 상황에서 역광을 받는 경 우와 야간과 같은 상황에서 부두와 선박 내부의 강한 조명에 의해 차량이 식별되지 않는 한계가 있었다. 안정적인 영상처리를 위해 충분 한 영상 데이터 확보와 프로그램 고도화가 필요해 보인다.

We propose a custom analysis technique for the dark field (DF) image based on transmission electron microscopy (TEM). The custom analysis technique is developed based on the DigitalMicrograph® (DM) script language embedded in the Gatan digital microscopy software, which is used as the operational software for most TEM instruments. The developed software automatically scans an electron beam across a TEM sample and records a series of electron diffraction patterns. The recorded electron diffraction patterns provide DF and ADF images based on digital image processing. An experimental electron diffraction pattern is recorded from a IrMn polycrystal consisting of fine nanograins in order to test the proposed software. We demonstrate that the developed image processing technique well resolves nanograins of ~ 5 nm in diameter.

In this study, we studied the damage area detection of the composite tension specimens under fatigue loading by using image processing techniques. The aim of this study is to detect the area of the damage region on the basis of original image. Basically we have used Matlab program. This study analyzed a total of six specimens under cyclic loading and the results using a user algorithm and analysis procedures of step 7. The damaged area was well detected except 3,000 cyclic loading. Accuracy of damage area detection is determined to be excellent by 83.3%(5/6). In general, however, in order to automatically detect the damaged area must develop an algorithm for setting the number of multi-threshold automatically. This is to perform the studies in the future.

This paper introduces a digital image processing(DIP) method as a method for measuring the displacement of pylon. The comparison of DIP results and ANSYS analysis results verified the validity of the image processing technique. Normalized cross-correlation(NCC) coefficient was used and experiments were performed three times. It shows that the displacement difference was 22% and 5% compared to ANSYS results. Therefore, the image processing method is expected to be able to measure the displacement of pylon sufficiently.

A three-dimensional digital image processing technique is proposed to quantitatively predict the dispersion phenomena of oil droplet onto the surface of the water. This technique is able to get the dispersion rate of an oil droplet three-dimensionally just below the surface of the water over time. The obtained dispersion rate obtained through this technique is informative to the investigation into the relationship among the gravity, surface tensions between oil, water, and air. This technique is based upon the three-dimensional PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a three CCD(Charge Coupled Device) cameras, an image grabber, and a host computer in which an image processing algorithm is adopted for the acquisition of dispersion rate oil an oil droplet.

하상재료 조사는 유사량 계산 및 하상변동과 같은 하도 계획에 필요한 기초 자료로서 입도분포, 비중, 다공성 등을 조사하는 것이다. 원칙적으로, 조사 지점은 하천 종단 방향으로 1 km 간격이고 하나의 횡단면에 3 개 이상이다. 따라서 조사 대상 하천의 종단 길이에 따라 조사 지점이 아주 많아지기 때문에 조사에 소요되는 시간과 비용이 상당히 증가한다. 본 연구는 입도분석법인 체적법과 화상해석법의 작업 효율성과 비용을 비교하고, 화상해석법의 적용 가능성을 검토하였다. 화상해석법에 의하여 환산된 등가원의 직경이 하상재료 입도분석에 적용될 수 있음을 확인하였다. 또한, 체적법과 화상해석법의 작업효율성과 비용을 분석한 결과 약 80%의 절감효과가 있음을 입증하였다.

In this study, the image processing technique referred as night vision was introduced in order to measure the displacement of structure during the nighttime. The validation of the reliability and the applicability of proposed method was evaluated by the scaled model test.

In this paper, we propose an image-based measurement method of structure dynamic characteristics to assess the damage of structure in a more cost-effective way than traditional structure health monitoring system.

This paper presents the image processing technique for detecting the aggregate shape. From the verification test, it was exhibited that the shape of aggregate can be detected by the developed program.

This paper presents the image processing technique for analyzing quantitatively air voids in paste. From the test, the performance of proposed technique was verified.