• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.135-141
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• 2019

The purpose of this study was to analyze the direct measurement data of 20-25 years male university students of 7th Size Korea data and to characterize and to type the body shape of lower body. It was to provide basic data for male university students' pants pattern production. The lower body part consisted of the 'horizontal factor' of the lower body composed of circumference, thickness, width, and 'vertical factor' of the lower body composed of the length and height. This was consistent with the analysis of the body shape factor of the lower half of male adolescents. The lower body shape was classified into four types. Type 1 was thick and relatively long in the lower body and was named 'thick long leg'. Type 2 was named 'short bird legs' because the lower body was thin and relatively short. Type 3 was relatively thin and long, so the lower body was named 'long crane leg'. In Type 4, the lower body was relatively thick and short, which means 'short pillar leg'. In the case of 20-25 year-old male university students, they have different body shapes depending on the girth and length of the lower half of their body as they have reached adulthood. Therefore, it would be necessary to provide a sales system that allows the repair of the length of the pants to be facilitated, and the length of the pants to be repaired when the pants are selected according to the circumference. Future studies will need to classify the body shape according to angle and flatness.

• 한국멀티미디어학회논문지
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• 제23권10호
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.

• 한국멀티미디어학회논문지
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• 제19권10호
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• pp.1775-1781
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• 2016

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. In addition, various signal processing techniques have been studied to extract feature vectors which are less sensitive to the location of the receiver. In this paper, we synthesized active echo signals using 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to echo signals to extract signal features. For the performance verification, classification experiments were performed using backpropagation and probabilistic neural network classifiers based on single aspect and multi-aspect method. As a result, we obtained a better recognition result using proposed feature extraction and multi-aspect based method.

• 한국멀티미디어학회논문지
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• 제21권6호
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• pp.659-666
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• 2018

The classification of the tablets recovered according to prescription changes is usually carried out manually by a number of pharmacists at the hospitals. Relatively high-wage pharmacists carry out the reclassification of the tablets, which results in a large loss of time and labor, and if the tablets are incorrectly classified, this can lead to medical accidents. In order to overcome these problems, a new automatic tablet classifying machine has been introduced. In the conventional automatic tablet classifying machine, tablets having various shapes, sizes, and colors are transferred to a classifying machine through the line feeder. Problems such as breakaway of the tablets from the line feeder, pilling of the tablets in the line feeder, and appearance contamination of the tablets occur. In this paper, we propose a system that automatically classifies the shape, size, and color of tablets through individual supply method by vacuum adsorption and image processing.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.

• 반도체디스플레이기술학회지
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• 제23권1호
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• pp.61-64
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• 2024

As research on autonomous driving technology becomes more active, various studies on signal recognition of traffic lights are also being conducted. When recognizing traffic lights with different purposes and shapes, such as pedestrian traffic lights, vehicle-only traffic lights, and right-turn traffic lights, existing classification methods may cause misrecognition problems. Therefore, in this study, we studied a model that allows accurate signal recognition by subdividing the classification of signals according to the purpose and type of traffic lights. A signal recognition model was created by classifying traffic lights according to their shape and purpose into horizontal, vertical, right turn, etc., and by comparing them with the existing signal recognition model based on YOLOv5, it was confirmed that more correct and accurate recognition was possible.

• 한국의류산업학회지
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• 제15권1호
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• pp.130-137
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• 2013

The percentage of overweight people has increased in older people due to the change of body shape (including pregnancy and giving birth for women). Obesity is accompanied by body shape changes; subsequently, there are more pattern design considerations compared to standard body shapes. This paper classifies the upper body shape of overweight women in Korea, analyzes features by body shape and proposes basic pattern design data that reflects the features of plus-size women body shapes. The data on 540 subjects in the overweight group (from 20 to 69 years old)whose BMI was over 25 was selected. The following features by shape were identified in accordance with the upper body shape classification of overweight women. Body Shape1 had lower body obesity with long stature and arms in proportion to the trunk length and represented 22.2% of the subjects. Body Shape2 had most parts near average sizes for overweight body shapes with short height and arms that represented 37.6% of the subjects (the highest ratio). Body Shape3 was the smallest body shape in the four groups with the most distinct body figure and represented 30.7% of the subjects. Body Shape4 (9.4% of the subjects)was the upper body obesity type (the fattest group)and with of the waist bigger abdominal obesity type.

• 한국콘텐츠학회논문지
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• 제16권7호
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• pp.31-41
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• 2016

하이퍼스펙트럴 영상을 이용하여 토지피복 분류를 정확히 수행하기 위해서는 전처리 작업으로서 대기보정을 거쳐야 한다. 항공 하이퍼스펙트럴 영상에 대하여 대기보정을 실시하고 대기보정 유 무에 따른 해수, 갯벌, 식생, 아스팔트, 콘크리트 등의 토지피복 항목별 분광반사율 특성을 비교하여 대기보정의 뚜렷한 효과를 확인할 수 있었다. 대기보정 후의 영상에 대하여 최대우도법, 분광각맵퍼법 등의 화소기반 감독분류기법으로 각각 토지피복 분류를 행하고 그 결과를 비교하였다. 분광각맵퍼법의 경우 임계각 $0.4^{\circ}$에서 노이즈를 최소화하면서 해수영역을 가장 양호하게 분류해 낼 수 있었다. 같은 개체라도 다양한 분광특성을 나타내는 하이퍼스펙트럴 영상의 경우 연안지역에서는 종래의 화소기반 분류기법보다는 축척, 분광 정보, 형태, 결 등을 종합적으로 고려하는 객체기반 분류기법이 더 우월할 것으로 사료된다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2000년도 춘계 학술대회지
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• pp.98-99
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• 2000

• 치과방사선
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• 제18권1호
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• pp.203-212
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• 1988

This study was designed to observe mandibular condyle shape and position in an asymptomatic popular ion. Using Accurad-200 head holder(Denar Corp.) for transcranial radiography of the temporo-mandibular joint region, transcranial radiographs were taken at the centric occlusion and 1 inch mouth opening in 73 males and females who were asymptomatic for TMJ disturbances, had no severe carious or missing teeth, and no history of prosthodontic or orthodontic treatments. Mandibular condyles were classified morphologically at the centric occlusion and evaluated in positional relationship with mandibular fossa and articular eminence at the centric occlusion and 1 inch mouth opening. The results were as follows: 1. In the morphologic classification of mandibular condyle, the convex shape was more prevalent in an asymptomatic population(90.4%), the locally concave shape and wedge shape were 5.5%, 4.1%. 2. At the centric occlusion, the means of joint space were 3.43nm superiorly, 2.17㎜ anteriorly, and 2.61㎜ posteriorly. 3. At the centric occlusion, the mandibular condyles were placed slightly anterior to the center of their fossa. 4. At the 1 inch mouth opening, the mandibular condyles were placed anterior to the articular eminence more than posterior to or below the top of the articular eminence.