• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.65-68
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• 2011

이 논문에서는 모래의 주성분을 분석하여 콘크리트 배합설계용의 적합성을 판별하는 시험방법을 제안한다. 주성분을 분석하는 방법은 자연모래와 부순 모래, 그리고 혼합모래에 포함된 유해물(점토, 마사토, 염화물)의 패턴을 분석하여 정지영상에서 유해물 비율을 나타내고자 한다. 영상으로 판독된 유해물 비율은 도로공사 품질시험기준에 의해 시험된 데이터와 비교하여 근접한 값을 도출해 내어 건설 자재인 모래에 섞여있는 유해물질을 검출해 내는 알고리즘을 제시한다.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.11a
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• pp.205-206
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• 2001

• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.166-175
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• 2020

Purpose This study aimed to compare the image quality and adverse events between Iopamidol 250 and Ioversol 320 usage during transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma (HCC). Materials and Methods Medical records and hepatic angiography from 113 patients who underwent TACE with Iopamidol 250 (44 patients) and Ioversol 320 (69 patients) were retrospectively reviewed. Vessel perception on hepatic angiography was graded into three categories by two radiologists for hepatic subsegmental arteries, the right gastroepiploic artery, right gastric artery, and pancreaticoduodenal artery. Imaging concordance was assessed by comparing the number of detected HCCs on hepatic angiography and CT. The adverse events before and after hepatic angiography were evaluated. Results The mean vessel perception scores were 2.92 and 2.94 for Iopamidol 250 and Ioversol 320, respectively. The imaging concordance was 31 (70.5%) and 46 (66.7%) patients for Iopamidol 250 and Ioversol 320, respectively. There were no statistical differences in vessel perception or imaging concordance (p > 0.05). One and six patients experienced nausea for Iopamidol 250 and Ioversol 320, respectively. There was no statistical difference in adverse events (p = 0.24). Conclusion Iopamidol 250 can be used in hepatic angiography for TACE without significant difference in image quality or occurrence of adverse events from Ioversol 320.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1822-1828
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• 2006

A key-frame should be efficiently selected to distinguish bad information from the videos. A previous technique selecting a key-frame mostly consists of the transformation scene-centered. In the case of harmful videos containing the quaility of continuous changes, the technique makes the total rate be reduced by an unnecessary key-frame. This thesis suggests the technique selecting a key-frame, an entry of the distinguishing system by using the quality of changes between the frames. In the experiment of this technique, it was proved that over 90% of the bad information was distinguished by the selected key frame, and also time efficiency was proved by showing 68% of decrement compared to the numbers I-frame. Therefore, This technique makes the system efficient to distinguish bad information, and efficiently can contribute to the distribution of the healthy movie information.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.349-351
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• 2005

현재 다양한 인터넷 콘텐츠들에 의해 많은 정보가 공유되고 있으며, 유익한 정보들과 더불어 성인물과 같은 유해한 정보들이 있다. 이로 인하여 여러 문제점들이 야기되고 있으며, 이를 해결하기 위해 다양한 방법들이 제안되고 있다. 그 중에서 성인 영상 차단을 위한 연구도 많이 행해지고 있으며 주로 색상을 이용한 방법을 사용하고 있다. 그러나 살색과 유사한 영상이나 노출이 심한 영상에는 성인 영상 검출의 신뢰성이 떨어지는 단점을 갖는다. 본 논문에서는 이런 문제점을 해결하기 위해 새로운 성인 영상 차단 방법을 제안한다. 기존의 제안된 살색 검출을 이용한 방법을 기반으로 성인 영상물로 판정될 수 있는 신체 부위를 검출함으로써 강인한 성인 영상 차단을 한다. 신체 부위에 대한 판별을 위해 여러 기저 영상에서 특징 벡터를 추출하고. 이 벡터를 Back Propagation(BP) 신경망의 데이터로 이용하여 학습한다. 제안한 성인 영상 차단 방법의 성능을 여러 장의 살색과 유사한 색상의 물체 영상과 노출이 심한 영상, 성인 영상을 이용한 종합적인 실험 결과인 성인 영상 검출률을 통해 증명한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2185-2191
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• 2015

With the advance of the environment where we can get various multimedia contents, adult image detection has become an important issue these days. In this paper, we suggest a method of robustly detecting navel areas from input images which can be usefully utilized in adult image detection. The suggested algorithm first extracts face regions and extracts candidate nipple areas using a nipple map. Our method then selects only actual nipple regions by filtering candidate areas with geometrical features and an average nipple filter. Subsequently, the method robustly detects navel areas by using the structural relation with the nipple areas and applying edge and saturation images. Experimental results show that the suggested algorithm can effectively detect navel regions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6708-6714
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• 2015

Various types of multimedia contents have been widely spread and distributed with the Internet that is easy to use. Meanwhile, Multimedia contents can bright a social problem because juveniles can access such harmful contents easily through the Internet. This paper proposes a method to determine if an input image is harmful or not, using an neural network. The proposed method first detects a face region from an input image through MCT features. The method then extracts skin color regions using color features and obtains candidate nipple areas from the extracted skin regions. Subsequently, we determine if the input image is harmful, by filtering out non-nipple regions using the artificial neural network. Experimental results show that the proposed method can effectively determine the harmfulness of input images.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.113-121
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• 2017

Due to the development of IT technology, harmful multimedia contents are spreading out. In addition, obscene and violent contents have a negative impact on children. Therefore, in this paper, we propose a multimodal approach for blocking obscene and violent video contents. Within this approach, there are two modules each detects obsceneness and violence. In the obsceneness module, there is a model that detects obsceneness based on adult and racy score. In the violence module, there are two models for detecting violence: one is the blood detection model using RGB region and the other is motion extraction model for observation that violent actions have larger magnitude and direction change. Through result of these three models, this approach judges whether or not the content is harmful. This can contribute to the blocking obscene and violent contents that are distributed indiscriminately.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.175-182
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• 2021

The purpose of this paper is to develop a machine learning-based marine drone to prevent the farming from harmful birds such as ducks. Existing drones have been developed as marine drones to solve the problem of being lost if they collide with birds in the air or are in the sea. We designed a CNN-based learning algorithm to judge harmful birds that appear on the sea by maritime drones operating by autonomous driving. It is designed to transmit video to the control PC by connecting the Raspberry Pi to the camera for location recognition and tracking of harmful birds. After creating a map linked with the location GPS coordinates in advance at the mobile-based control center, the GPS location value for the location of the harmful bird is received and provided, so that a marine drone is dispatched to combat the harmful bird. A bird fighting drone system was designed and implemented.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.63-64
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• 2014

본 논문에서는 성인영상에서 모자이크 검출 기법을 제안한다. 먼저 성인영상에 가장 많이 사용되는 격자형 모자이크 검출을 위하여 입력영상에서 에지를 검출한 후, 에지영상을 이용하여 모자이크 후보영역을 검출한다. 모자이크 후보영역은 모자이크맵을 생성하고 이진화하여 후보영역을 산출한다. 이렇게 산출된 후보영역내의 모자이크맵의 값이 임계치 이상인 영역을 최종 모자이크 영역으로 검출한다. 실험결과 모자이크가 없는 영상에서 약간의 오검출이 있었으나, 전체적으로 우수한 성능을 보였다.