• 한국전자통신학회논문지
• /
• 제19권1호
• /
• pp.327-334
• /
• 2024

본 논문에서는 라즈베리파이 기반으로 손바닥 정맥혈관 이미지를 획득하기 위하여 950nm파장을 가지는 근적외선 LED 광원 장치와 손금을 획득하기 위한 백색 LED 광원 장치를 가지는 시스템을 개발하였다. 또한 획득한 정맥 및 손금 이미지에 대하여 영상 전처리 과정(흑백화, 평활화, 이진화, 블러링, 세선화 등)을 통하여 정맥과 손금이 혼합된 위조 방지 및 보안이 강화된 고유 패턴이 추출 가능한 영상처리 기술을 구현하여 보안성이 강화된 시스템에서 활용할 수 있는 원천 기술을 확보하였다.

• 한국농업기계학회:학술대회논문집
• /
• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
• /
• pp.621-631
• /
• 1996

It is said that robot can be used for multi-purpose use by changing end effector or/and visual sensor with its software. In this study, it was investigated what multi-purpose robot for fruit-production was using a tomato harvesting robot and a robot to work in vineyard. Tomato harvesting robot consisted of manipulator, end-effector, visual sensor and traveling device. Plant training system of larger size tomato is similar with that of cherry-tomato. Two end-effectors were prepared for larger size tomato and cherry-tomato fruit harvesting operations, while the res components were not changed for the different work objects. A color TV camera could be used for the both work objects, however fruit detecting algorithm and extracted features from image should be changed. As for the grape-robot , several end-effector for harvesting , berry thinning , bagging and spraying were developed and experimented after attaching each end-effector to manipulator end. The manipulator was a polar coordinate type and had five degrees of freedom so that it could have enough working space for the operations. It was observed that visual sensor was necessary for harvesting, bagging and berry-thinning operations and that spraying operation requires another sensor for keeping certain distance between trellis and end-effector. From the experimental results, it was considered that multi-operations by the same robot could be appropriately done on the same or similar plant training system changing some robot components . One of the important results on having function of multi-operation was to be able to make working period of the robot longer.

• 한국방사선학회논문지
• /
• 제2권1호
• /
• pp.23-29
• /
• 2008

본 연구에서는 웨이블릿 변환과 경계선 검출 필터를 이용하여 초음파영상의 다해상도 분해를 한 후 경계선 검출 필터링을 통해 초음파 영상의 화질을 개선하는 방안을 제안하였다. 제안된 방법에서는 잡음을 줄이고 에지를 강화하기 위해 웨이블릿 변환된 영상으로부터 얻어진 저해상도 영상에서 고해상도 영상으로 단계적으로 영역별 선택계수 조정과 방향성을 고려한 에지 필터링을 수행하였다. 이를 통해 반점영역의 픽셀은 웨이블릿 계수를 줄여 에지를 제외한 영역에서 선택적 저역통과 필터링 효과를 만들고, 에지에서는 접선 방향으로 평활화를 하여 연속성을 향상시키고, 법선 방향으로는 세선화를 하여 contrast를 높였다. 실험을 통해 단일해상도에서 비선형적 이방성의 확산모델을 이용한 필터링 방법과 웨이블릿 수축구조를 이용한 필터링 방법에 대해 비교하였다.

• Journal of Biosystems Engineering
• /
• 제36권1호
• /
• pp.40-47
• /
• 2011

Image analysis algorithm for the quality evaluation of ginseng seedling was investigated. The images of ginseng seedling were acquired with a color CCD camera and processed with the image analysis methods, such as binary conversion, labeling, and thinning. The processed images were used to calculate the length and weight of ginseng seedlings. The length and weight of the samples could be predicted with standard errors of 0.343 mm, and 0.0214 g respectively, $R^2$ values of 0.8738 and 0.9835 respectively. For the evaluation of the three quality grades of Gab, Eul, and abnormal ginseng seedlings, features from the processed images were extracted. The features combined with the ratio of the lengths and areas of the ginseng seedlings efficiently differentiate the abnormal shapes from the normal ones of the samples. The grade levels were evaluated with an efficient pattern recognition method of support vector machine analysis. The quality grade of ginseng seedling could be evaluated with an accuracy of 95% and 97% for training and validation, respectively. The result indicates that color image analysis with support vector machine algorithm has good potential to be used for the development of an automatic sorting system for ginseng seedling.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.1315-1318
• /
• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1991년도 하계학술대회 논문집
• /
• pp.900-904
• /
• 1991

In this paper, our study for the recognition of Hand-written Korean characters, Arabic numbers and alphabets by neural netwoks. This System extracts feature of character by using the MESH feature point of handwritten character, Arabic numbers and alphabets. To reduce the input image data, features are extracted from each input images. A MLP(multi-layer perceptron) with one hidden layer was trained with a modified BEP(back error propagation) algorithm. This method extracts feature sets of the characters directly from the scanner and can enhance computation speed without using the special preprocesses such as size normalization, smoothing, and thinning.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.900-903
• /
• 1996

The objective of this paper is to make the weighted graph map for path planning using the ultrasonic sensor measurements that are acquired when an A.M.R (autonomous mobile robot) explores the unknown circumstance. First, The A.M.R navigates on unknown space with wall-following and gathers the sensor data from the environments. After this, we constructs the occupancy grid map by interpreting the gathered sensor data to occupancy probability. For the path planning of roadmap method, the weighted graph map is extracted from the occupancy grid map using morphological image processing and thinning algorithm. This methods is implemented on an A.M.R having a ultrasonic sensor.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 2003년도 가을 학술발표회 논문집
• /
• pp.655-658
• /
• 2003

The crack of concrete structure plays an important role in the durability and safety of structure. Therefore, the features such as width, length, and direction of that must be measured periodically. The conventional method of measurement of cracks is manually sketched, however. it takes a fairly long time and lacks quantitative objectivity. This study proposes the algorithm to extract and analyze cracks automatically. The proposed algorithm is composed of two sub-algorithms. The extraction algorithm includes elimination of effect due to light, binarization. and noise reduction. The analysis algorithm includes thinning process, labeling, and calculation of crack width, length, and direction. The test to demonstrate the algorithm is fulfilled using the images of cracks on real concrete surface.

• 한국정보통신학회논문지
• /
• 제6권2호
• /
• pp.346-355
• /
• 2002

이 연구는 인식의 정확성을 향상시키기 위하여 단일생체 인식 대신에 얼굴, 입술, 음성을 이용하는 다중생체 인식방법을 제안한다. 각 생체 특징은 다음과 같은 방법으로 찾는다. 얼굴 특징은 웨이블렛 다중분해와 주성분 분석방법으로 계산하였고, 입술의 경우는 입술의 경계를 구한후 최소 자승법을 이용한 방정식의 계수를 구하였으며, 음성은 멜 주파수에 의한 MFCC를 사용하였으며, 역전파 학습 알고리즘으로 분류하여 실험하였다. 실험을 통해 본 방법의 유효성을 확인하였다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
• /
• pp.34-36
• /
• 2009

This paper proposes an effective lane detection algorithm using hugh transform and lane model. The proposed lane detection algorithm includes two major components, i.e., lane marks segmentation and an exact lane extraction using a novel postprocessing technique. The first step is to segment lane marks from background images using HSV color model. Then, a novel postprocessing is used to detect an exact lane using Hugh transform and lane models(linear and curved lane models). The postprocessing consists of three parts, i.e, thinning process, Hugh Transform and filtering process. We divide input image into three regions of interests(ROIs). Based on lane curve function(LCF), we can detect an exact lane from various extracted lane lines. The lane models(linear and curved lane mode]) are used in order to judge whether each lane segment is fit or not in each ROIs. Experimental results show that the proposed scheme is very effective in lane detection.