• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
• /
• pp.434-436
• /
• 2006

In a visual driver-assistance system, separating moving objects from fixed objects are an important problem to maintain multiple hypothesis for the state. Color and edge-based tracker can often be "distracted" causing them to track the wrong object. Many researchers have dealt with this problem by using multiple features, as it is unlikely that all will be distracted at the same time. In this paper, we improve the accuracy and robustness of real-time tracking by combining a color histogram feature with a brightness of Optical Flow-based feature under a Sequential Monte Carlo framework. And it is also excepted from Tracking as time goes on, reducing density by Adaptive Particles Number in case of the fixed object. This new framework makes two main contributions. The one is about the prediction framework which separating moving objects from fixed objects and the other is about measurement framework to get a information from the visual data under a partial occlusion.

• Journal of information and communication convergence engineering
• /
• 제15권4호
• /
• pp.250-255
• /
• 2017

In this paper, we propose a method of detecting the region for measuring intima-media thickness (IMT). The existing methods for IMT measurement are automatic, but the region used for measuring IMT is not detected automatically but often set by the user. Therefore, research on detecting the intima-media region is needed for fully automated IMT measurement. The proposed method uses a morphological feature of the carotid artery visible as two long high-brightness horizontal lines at the upper and lower parts. It uses Gaussian blurring, ends-in search stretching, color quantization using a color-importance-based self-organizing map, and morphological operations to emphasize and to detect the morphological feature. The experimental results for evaluating the performance of the proposed method showed a 97.25% (106/109) success rate. Therefore, the proposed method can be used to develop a fully automated IMT measurement system.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 추계학술대회논문집A
• /
• pp.559-563
• /
• 2000

In this paper we describe a method for aligning a robot gripper using image information. The region of gripper is represented from HSI color model that has major advantage of brightness independence. In order to extract the feature points for vision based position control, we find the corners of gripper shape using polygonal approximation method which determines the segment size and curvature of each points. We apply the vision based scheme to the task of alignment of gripper to reach the desired position by 2 RGB cameras. Experiments are carried out to exhibit the effectiveness of vision based control using feature points from polygonal approximation of gripper.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 하계학술대회 논문집 D
• /
• pp.2634-2636
• /
• 2001

This paper proposes a new method of retrieving images from large image databases. The method is based on VQ(Vector Quantization) of local texture information at interest points automatically detected in an image. The texture features are extracted by Gabor wavelet filter bank, and rearranged for rotation. These features are classified by VQ and then construct a pattern histogram. Retrievals are performed by just comparing pattern histograms between images. Experimental results have shown the robustness of the proposed method to image rotation, small scale change, noise addition and brightness change and also shown the possibility of the retrieval by a partial image.

• Journal of Information Processing Systems
• /
• 제19권3호
• /
• pp.370-376
• /
• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권4호
• /
• pp.980-997
• /
• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

• 한국멀티미디어학회논문지
• /
• 제15권2호
• /
• pp.195-203
• /
• 2012

본 논문은 다중센서 영상을 이용한 결정 융합 기반의 지상 표적 분류 알고리즘 및 특징 추출 기법을 제안한다. 표적의 인식률 향상을 위하여 가중 투표 방법을 적용함으로써 개별 분류기로부터 획득된 결과를 융합하였다. 또한 개별 센서 영상 내에 속한 표적을 분류하기 위해 CCD 영상으로부터 획득한 CM 영상의 밝기 차이와 FLIR 영상 내 표적의 윤곽선 정보 및 차량과 포탑의 너비 비율을 이용하여 스케일과 회전변화에 강인한 특징들을 추출하였다. 마지막으로 실험을 통하여 본 논문에서 제안한 지상 표적 분류 알고리즘과 특징 추출 기법에 대한 성능을 검증한다.

• 한국컴퓨터그래픽스학회논문지
• /
• 제21권5호
• /
• pp.1-10
• /
• 2015

본 연구는 가상 조경을 구성하는 다양한 종류의 디지털 잎을 쉽고 직관적으로 제작할 수 있는 저작도구 개발방법을 제안한다. 제안하는 저작도구의 핵심 시스템은 영상 워핑기반의 잎몸 윤곽선 변형 방법, 잎맥의 절차적 모델링 그리고 잎의 색과 명암 등을 표현하기 위한 수리모델기반 시각화 방법으로 구성된다. 우선 잎 영상을 입력으로 받아 잎몸에 대한 윤곽선 정보를 찾고, 특징기반 영상 워핑을 활용하여 다양한 잎몸 형상을 직관적인 구조에서 쉽게 생성할 수 있는 잎몸 변형 방법을 설계한다. 그리고 계산된 잎몸 윤곽선을 기반으로 잎몸 형상에 적합한 자연스러운 잎맥 패턴을 생성하는 일반화된 절차적 모델링 방법을 저작도구에 맞게 구현한다. 마지막으로 약수 함수의 합성 기반의 수리모델을 활용하여 잎의 색, 명암 그리고 시간에 따른 변화를 표현할 수 있는 시각화 기능을 적용한다. 제안한 저작도구를 활용하여 제작된 디지털 잎이 다양한 3차원 디지털 콘텐츠 분야에 활용 가능하도록 텍스쳐 지원 기능을 제공한다.

• Journal of Biosystems Engineering
• /
• 제29권1호
• /
• pp.71-78
• /
• 2004

Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

• Journal of the Korean Wood Science and Technology
• /
• 제37권6호
• /
• pp.556-565
• /
• 2009

제재목 육안등급판정 자동화시스템은 정확한 입력 화상이 요구된다. 이송 중인 재장 3.6 m의 국내산 소나무의 제재목 화상을 생성시키기 위해서 영역카메라를 이용하여 부분 화상을 획득하였고 2종류의 템플릿 위치지정법과 6가지의 템플릿 크기 조건을 적용하여 병합하였다. 특징영역 추출법이 템플릿 고정법에 비해 병합 성능이 우수하였다. 길이오차의 발생 요인은 명도차이, 특정 패턴, 템플릿 크기 등에 의한 유사도 하락에 있었다. 부정합은 길이가 길고 반복적인 목리에서 주로 발생하였다. 템플릿 크기는 6가지 템플릿 종류 중에 크기가 가장 작은 $100{\times}100$ 화소가 가장 병합 성능이 우수하였다. 병합 성능을 향상시키기 위해서는 정밀한 템플릿의 크기 선정과 명도 차이를 감소시킬 수 있는 화상병합 전처리에 대한 연구가 요구된다.