• Journal of Information Processing Systems
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• v.16 no.3
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• pp.629-638
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• 2020

In this paper, an unmanned automation system for harvesting chili peppers through image recognition in the color space is proposed. We developed a cutting-edge technology in terms of convergence between information and communication technology (ICT) and agriculture. Agriculture requires a lot of manpower and entails hard work by the laborers. In this study, we developed an autonomous application that can obtain the head coordinates of a chili pepper using image recognition based on the OpenCV library. As an alternative solution to labor shortages in rural areas, a robot-based chili pepper harvester is proposed as a convergence technology between ICT and agriculture requiring hard labor. Although agriculture is currently a very important industry for human workers, in the future, we expect robots to have the capability of harvesting chili peppers autonomously.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.106-110
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• 2002

4S-Van is being developed in order to provide the spatial data rapidly and accurately. 4S-Van technique is a system for spatial data construction that is heart of 4S technique. Architecture of 4S-Van system consists of hardware integration part and post-processing part. Hardware part has GPS, INS, color CCD, camera, B/W CCD camera, infrared rays camera, and laser. Software part has GPS/INS integration algorithm, coordinate conversion, lens correction, camera orientation correction, and three dimension position production. In this paper, we suggest that adequate 4S-Van design is needed according to application environment from various test results.

• Journal of KIISE:Software and Applications
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• v.28 no.3
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• pp.285-297
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• 2001

본 논문에서는 특정한 객체의 색 분포 모델링으로부터 얻어지는 가중 색 히스토그램과 지배적인 색의 영상공간 분포특성을 이용한 내용기반 영상 검색 방법을 제안한다. 특정한 객체의 예로 사람 얼굴을 선택했고, 그것의 색 분포를 u*-v* 색도 공간에서 모델링 했으며, 모델의 정규화된 부피를 균등 양자화된 색도 공간의 각 빈(bin)의 히스토그램 값에 대한 가중치로 결정하고, 결정된 가중치를 히스토그램 정합 과정에 적용하였다. 또한 색 히스토그램 값이 큰 특정한 수의 빈으로 정의되는 지배적인 색의 영상 공간 분포를 가중 색 히스토그램과 함께 유사성의 측정기준으로 사용하였다. 제안한 검색 방법을 500여개의 영상에 대해 실험한 결과 제안한 방법이 얼굴을 포함하는 영상을 질의로 주었을 때 얼굴을 포함하는 영상을 우선적으로 찾는데 효과적임을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.311-312
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• 2011

사람은 어느 누구에게나 본인이 좋아하는 색상이 선천적으로 존재하고 후천적으로 혹은 인위적으로도 존재한다. 본 논문에서는 사람이 좋아하고 사람에게 어울리는 색상을 찾는 방법에 대하여 제시한다. 먼저, 피부, 머리카락, 눈동자의 색과 같이 색상의 기본을 이루는 톤(tone)에 대하여 알아보도록 한다. 그리고 색을 봄, 여름, 가을, 겨울의 사계절로 나누어 피부의 색, 머리카락의 색, 눈동자의 색과 자기 자신이 기호하거나 좋아하는 것과 본인의 성격에 따라서 나누어지는 사계절 색채이론을 설명한다. 또한 각 계절별 컬러의 특성도 살펴보도록 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.313-314
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• 2011

우리가 사는 세계에는 무수히 많은 색들이 존재한다. 이 수많은 색들은 인간에게 항상 의미있는 지시나 신호를 보내고 있다. 본 논문에서는 이러한 인간이 좋아하는 색과 인간의 성격에 대해 자세히 알아본다. 우리 인간은 거의 무의식적으로 색채에 반응하고 색채의 영향을 받고 있다. 색채들이 우리 인간에게 주는 효력은 무시할 수 없을 정도로 엄청나게 크다. 인간은 어떠한 색채를 보고 무드가 좋아지거나 가라앉기도 하고 또는 밝아지거나 나아지기도 한다. 이것은 인간은 빛으로부터 색이 주는 지시나 신호를 알아듣는 것이다. 색채의 지시나 신호를 인식하거나 자각하여 받아들인다면 색채가 지닌 일반적인 뜻을 알 수 있으며 효율적으로 색채를 사용할 수 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.309-310
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• 2011

자동차를 사러 매장에 갔을 때 우리는 자동차의 색상에 따른 교통사고의 발생 확률과 무관하게 자동차의 성능이나 디자인과 또는 자동차의 가격이나 안정성 등을 최우선으로 꼽고 자동차를 선택한다. 본 논문에서는 자동차의 색인 파랑, 녹색, 흰색, 빨강, 검정, 황색의 차량을 대상으로 색상별로 사고 내역을 조사하여 사고가 발생할 확률이 가장 높은 색부터 가장 낮은 색까지를 차례로 제시한다. 사고가 많고 적음은 색에서 진출색과 후퇴색의 차이로서, 사고가 많이 나는 색이나 사고 나기 쉬운 색은 실제보다 멀리 있는 것처럼 보이는 후퇴색이고, 사고가 적은 색은 실제보다 더 가까이 있는 것처럼 보이는 진출색임을 알 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.49-55
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• 2018

In this paper, we propose a design and development of instructional cards to understand the grammar of coding, solving the problems and extending the computational thinking in the robot-driven environment. First, we designed the input/output module of the robot to process the coding grammar through the function analysis of the robot. And we designed the module of command card to learn coding grammar using color sensors. We have proven the validity of the designed instruction card by examining the experts to see if it is suitable for coding grammar learning. Designed robot and command card were developed with 28 cards and sensor robot. After applying the developed robot and command card to the elementary school students, the questionnaire showed that students grow the understanding and confidence of coding. In addition, students showed an increased need for programming learning.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.131-136
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• 2018

This paper proposes a computer-aided diagnostic algorithm in a non-invasive way. Currently, clinical diagnosis of jaundice is performed through blood sampling. Unlike the old methods, the non-invasive method will enable parents to measure newborns' jaundice by only using their mobile phones. The proposed algorithm enables high accuracy and quick diagnosis through machine learning. In here, we used the SVM model of machine learning that learned the feature extracted through image preprocessing and we used the international jaundice research data as the test data set. As a result of applying our developed algorithm, it took about 5 seconds to diagnose jaundice and it showed a 93.4% prediction accuracy. The software is real-time diagnosed and it minimizes the infant's pain by non-invasive method and parents can easily and temporarily diagnose newborns' jaundice. In the future, we aim to use the jaundice photograph of the newborn babies' data as our test data set for more accurate results.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.280-286
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• 2024

In this paper, layered UNet with warmup and dropout tricks was used to segment teeth instantly by using data labeled for each individual tooth and increase performance of the result. The layered UNet proposed before showed very good performance in tooth segmentation without distinguishing tooth number. To do instance segmentation of teeth, we labeled teeth CBCT data according to tooth numbering system which is devised by FDI World Dental Federation notation. Colors for labeled teeth are like AI-Hub teeth dataset. Simulation results show that layered UNet does also segment very well for each tooth distinguishing tooth number by color. Layered UNet model using warmup trick was the best with IoU values of 0.80 and 0.77 for training, validation data. To increase the performance of instance segmentation of teeth, we need more labeled data later. The results of this paper can be used to develop medical software that requires tooth recognition, such as orthodontic treatment, wisdom tooth extraction, and implant surgery.

• Progress in Medical Physics
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• v.21 no.2
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• pp.153-164
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• 2010

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.