• Smart Media Journal
• /
• v.13 no.2
• /
• pp.52-61
• /
• 2024

In the shipyard, aerial images are acquired at regular intervals using Unmanned Aerial Vehicles (UAVs) for the management of external storage yards. These images are then investigated by humans to manage the status of the storage yards. This method requires a significant amount of time and manpower especially for large areas. In this paper, we propose an automated management technology based on a semantic segmentation foundation model to address these challenges and accurately assess the status of external storage yards. In addition, as there is insufficient publicly available dataset for external storage yards, we collected a small-scale dataset for external storage yards objects and equipment. Using this dataset, we fine-tune an object detector and extract initial object candidates. They are utilized as prompts for the Segment Anything Model(SAM) to obtain precise semantic segmentation results. Furthermore, to facilitate continuous storage yards dataset collection, we propose a training data generation pipeline using SAM. Our proposed method has achieved 4.00%p higher performance compared to those of previous semantic segmentation methods on average. Specifically, our method has achieved 5.08% higher performance than that of SegFormer.

• Korean Journal of Clinical Laboratory Science
• /
• v.55 no.4
• /
• pp.261-268
• /
• 2023

[¹⁸F]Fluorocholine is a radiopharmaceutical used non-invasively in positron emission tomography to diagnose parathyroid adenoma, prostate cancer, and hepatocellular carcinoma by evaluating the choline metabolism. In this study, a radiolabeling method for [¹⁸F]fluorocholine was optimized using a solid phase extraction (SPE) cartridge. [¹⁸F]Fluorocholine was labeled in two steps using an automated synthesizer. In the first step, dibromomethane was reacted with [¹⁸F]KF/K2.2.2/K₂CO₃ to obtain the intermediate [¹⁸F]fluorobromomethane. In the second step, [¹⁸F]fluorobromomethane was passed through a Sep-Pak^Ⓡ Silica SPE cartridge to remove the impurities and then reacted with N,N-dimethylaminoethanol (DMAE) in a Sep-Pak^Ⓡ C18 SPE cartridge to label [¹⁸F]fluorocholine. The reaction conditions of [¹⁸F]fluorocholine were optimized. The synthesis yield was confirmed according to the number of silica cartridges and DMAE concentration. No statistically significant difference in the synthesis yield of [¹⁸F]fluorocholine was observed when using four or three silica cartridges (P>0.05). The labeling yield was 11.5±0.5% (N=4) when DMAE was used as its original solution. On the other hand, when diluted to 10% with dimethyl sulfoxide, the radiochemical yield increased significantly to 30.1±5.2% (N=20). In conclusion, [¹⁸F]Fluorocholine for clinical use can be synthesized stably in high yield by applying an optimized synthesis method.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.4
• /
• pp.15-24
• /
• 2007

The recognition of postal address images is indispensable for the automatic sorting of postal envelopes. The process of the address image recognition is composed of three steps-address image preprocessing, character recognition, address interpretation. The extracted character images from the preprocessing step are forwarded to the character recognition step, in which multiple candidate characters with reliability scores are obtained for each character image extracted. aracters with reliability scores are obtained for each character image extracted. Utilizing those character candidates with scores, we obtain the final valid address for the input envelope image through the address interpretation step. The envelope sorting rate depends on the performance of all three steps, among which character recognition step could be said to be very important. The good character recognizer would be the one which could produce valid candidates with very reliable scores to help the address interpretation step go easy. In this paper, we propose the method of generating character candidates with reliable recognition scores. We utilize the existing MLP(multilayered perceptrons) neural network of the address recognition system in the current automatic postal envelope sorters, as the classifier for the each image from the preprocessing step. The MLP is well known to be one of the best classifiers in terms of processing speed and recognition rate. The false alarm problem, however, might be occurred in recognition results, which made the address interpretation hard. To make address interpretation easy and improve the envelope sorting rate, we propose promising methods to reestimate the recognition score (confidence) of the existing MLP classifier: the generation method of the statistical recognition properties of the classifier and the method of the combination of the MLP and the subspace classifier which roles as a reestimator of the confidence. To confirm the superiority of the proposed method, we have used the character images of the real postal envelopes from the sorters in the post office. The experimental results show that the proposed method produces high reliability in terms of error and rejection for individual characters and non-characters.

• Journal of the Korea Computer Graphics Society
• /
• v.19 no.4
• /
• pp.1-11
• /
• 2013

In this paper, we represented the HTML5 webpage in 3D space for the 3D stereoscopic display by using CSS3 stylesheet; browser-based declarative contents, and proposed CSS Stereo 3DTV Profile. First, we suggested various webpage separation methods for reconstructing webpages in the 3D space effectively. Next, we suggested 3D view volume setting method by using extended CSS3 modules. And then, pre-processor converts sample contents which is written extended CSS stylesheet into the present CSS stylesheet for displaying in the webkit based browser. For the resulting stereoscopic images, we developed a rendering engine emulator which is implemented in JavaScript for simple display in the web browser, which produced dual images from virtual left and right-eyed cameras. And we have checked the sample contents displayed on the 3DTV.

• Journal of Digital Contents Society
• /
• v.19 no.6
• /
• pp.1207-1212
• /
• 2018

The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.8
• /
• pp.46-53
• /
• 1999

We have developed glove based hand gesture recognition system for recognizing 3D gesture of operators in remote work environment. Polhemus sensor attached to the PinchGlove is employed to obtain the sequence of 3D positions of a hand trajectory. These 3D data are then encoded as the input to our recognition system. We propose the use of the strokes to be modeled by HMMs as basic units. The gesture models are constructed by concatenating stroke HMMs and thereby the HMMs for the newly defined gestures can be created without retraining their parameters. Thus, by using stroke models rather than gesture models, we can raise the system extensibility. The experiment results for 16 different gestures show that our stroke based composite HMM performs better than the conventional gesture based HMM.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.6
• /
• pp.246-254
• /
• 2016

Thick-shell welding for super-sized oil storage tanks is currently done manually, which causes deterioration in quality and a lack of uniformity due to frequent rewelding. The limitations of the external environment must also be considered for manual welding. This paper describes the development of a carriage system for automatic vertical welding to increase reliability, reduce cost, and enhance productivity. The system consists of a welding platform, carriage device, and control unit, which were conceptually designed according to design specifications and manufactured with modular parts. In addition, the structure was analyzed for safety and to predict design problems in advance, and the results are reflected in reviewing the design. To evaluate the performance of the system, a tensile test, bending test, and weld time test were carried out, and the results were satisfactory. The time required for automatic weld was greatly improved by more than 87%, compared to the manual welding time.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.145-145
• /
• 2017

농작업 자세 중에서 중량물을 반복적으로 들고 내리는 자세는 요통과 같은 근골격계 질환의 유발행위로 분류된다. 이는 인간공학적 유해요인 평가도구에 의해 위험도 별로 정량화 할 수 있다. 이러한 평가방법은 농작업 자세를 개선하여 근골격계 질환을 예방할 수 있다는 측면에서 매우 중요하다. 그러나 기존의 작업자세 부하 평가방법들은 동적 자세를 평가하는데 있어 어려움이 있을 뿐 만 아니라 평가 과정에서 관찰자의 주관성이 개입 될 수 있다는 한계점을 갖고 있다. 이에 본 연구에서는 중량물을 들고 내리는 동적 자세에서 발생하는 부하를 Energy expenditure를 이용하여 평가할 수 있는 시스템을 개발하는 것이다. Energy expenditure는 체중, 성별 등과 같은 작업자 관련 변수와 중량물의 무게, 들어 올리는 높이, 빈도수 등과 같은 작업환경 관련 변수를 이용하여 최대 산소소비량을 예측하는 방법이다. 본 연구에서 제안하는 작업자 및 작업환경 관련 변수를 자동 측정하는 시스템은 초음파 거리측정 센서와 깔창 형태의 센서를 이용하여 구성하였다. 이를 통해 남성(6명), 여성(6명)을 대상으로 20kg의 중량물을 들고 내리는 동작에서 발생하는 Energy expenditure 값을 산출하였고, 산소소비량 측정 장비를 통해 획득된 최대 산소소비량($VO_2$)과 비교하여 검증하였다. 여성을 대상으로 한 Energy expenditure 값과 최대 산소소비량 간 상관관계는 0.984로 나타났으며, 남성의 경우에는 0.998로 높은 상관관계를 보였다. 이와 같은 에너지 대사율 평가시스템은 연속적이고 반복적인 실제 농작업 자세 부하를 동적인 상태에서 평가할 수 있을 뿐 만 아니라 산소소비량 측정기와 같은 추가적인 장비가 필요하지 않아 현장 적용성이 뛰어 날 것으로 기대된다.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.47-51
• /
• 2006

As the recent announcement of the functional cosmetics law, the need of studies on efficacy evaluation of skin related cosmetics and medical supplies has grown. Especially to identify skin improvement, we have to compare the exact parts of the skin, however up to now it is compared only by image matching that is appeared to the human eye. This study proposes the automatical image matching system for improving the accuracy of evaluation a skin improvement. Firstly we define the feature of the skin pores and wrinkles, and extract anticipation region from skin images. And then, we calculate moments for each extracted regions and classify them as pores and wrinkles. After that, we calculate the vector by computing centroids between each regions. Through this process, we compare the vector similarities and perform the matching between existing image and reference image. To verify the efficiency of the algorithm several experiments are conducted.

• Journal of KIISE:Software and Applications
• /
• v.30 no.5_6
• /
• pp.476-486
• /
• 2003

There is no explicit spelling change information in part-of-speech tagged corpora of Korean. It causes some difficulties in acquiring the data to study Korean morphology, i.e. automatically in constructing a dictionary for morphological analysis and systematically in collecting the phenomena of the spelling changes from the corpora. To solve this problem, this paper presents a method to recognize spelling changes between morphemes of a Korean word in tagged corpora, only using a string matching, without using a dictionary and phonological rules. This method not only has an ability to robustly recognize the spelling changes because it doesn't use any phonological rules, but also can be implemented with few cost. This method has been experimented with a large tagged corpus of Korean, and recognized the 100% of spelling changes in the corpus with accuracy.