• 디지털융복합연구
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• 제13권9호
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• pp.183-189
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• 2015

본 논문은 서베일런스 네트워크에서 영상의 색상 정보를 이용한 객체 추적 방법을 제안한다. 이 방법은 적응적인 색상 모델을 이용한 객체 검출을 수행한다. 객체 윤곽선 검출은 객체 인식과 같은 응용에서 중요한 역할을 수행한다. 실험 결과는 색상과 크기에서 객체의 다양한 변화가 있을 때에도 성공적인 객체 검출을 증명한다. 실시간으로 객체를 검출하는 응용 분야에서 대량의 영상 데이터를 전송할 때 색상 분포의 형태를 찾아내는 것이 가능하다. 객체의 특정 색상 정보는 입력 영상에서 동적으로 변화하는 색상에서 자주 수정되어진다. 그래서, 이 알고리즘은 해당 추적 영역 안에서 객체의 추적 영역 정보를 탐지하고 그 객체의 움직임만을 추적한다. 실험을 통해, 본 논문은 어떤 이상적인 상황하에서 제안하는 객체 추적 알고리즘이 다른 방법보다 더 강인한 면이 있다는 것을 보여준다.

• 한국멀티미디어학회논문지
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• 제10권7호
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• pp.827-837
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• 2007

기존의 색상 기반의 Mean Shift 알고리즘을 이용한 객체추적 알고리즘은 초기 색상 정보가 사라질 경우 정확한 객체추적을 수행할 수 없다. 본 논문은 객체의 색상이 변할 때 색상 정보를 변경하여 정확히 추적하는 알고리즘을 제안한다. 제안 알고리즘은 현재의 위치를 중심으로 다음 객체 위치에 해당하는 밀도가 가장 높은 위치를 Mean Shift알고리즘으로 구하고, 바꿔 색상 정보를 변경하는 반복적인 기법을 사용한다. 이를 통해 처음 설정한 객체의 색상이 바뀌거나 사라지더라도 정확한 객체추적을 할 수 있게 되었다. 본 논문에서는 제안 알고리즘을 구현하고, 실험 결과로 성능을 입증한다.

• 디지털산업정보학회논문지
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• 제13권1호
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• pp.125-133
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• 2017

Color in an image is determined by illuminant and surface reflectance. So, to recover unique color of object, estimation of exact illuminant is needed. In this study, the illumination models suggested to get the object color constancy with the physical illumination model based on physical phenomena. Their characteristics and application limits are presented and the necessity of an extended illumination model is suggested to get more appropriate object colors recovered. The extended illumination model should contain an additional term for the ambient light in order to account for spatial variance of illumination in object images. Its necessity is verified through an experiment under simple lighting environment in this study. Finally, a reconstruction method for recovering input images under standard white light illumination is experimented and an useful method for computing object color reflectivity is suggested and experimented which can be induced from combination of the existing illumination models.

• 정보처리학회논문지B
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• 제12B권7호
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• pp.721-728
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• 2005

본 논문에서는 영상 내 물체 영역에 대한 다중정규화와 움직임 색상 정보를 활용하여 이동 물체에 대한 후보 그룹을 추출하고 영상 분할 방법에 의해 대상 물체 영역을 정의하며 최종적으로 목표물체에 대한 검출방법을 제공하였다. 다중 색상변환에 의해 물체의 고유영역 확률을 강화하고 MCWUPC(Moving Color Weighted Unmatched Pixel Count) 연산을 활용하여 이동물체의 영역을 강조하는 두 가지 개념을 결합함으로써 최종적으로 입력 영상 시퀀스에서의 후보영역을 찾아 분할하였으며 매 프레임 정확한 물체의 외곽정보를 검출하였다. 제안된 알고리즘을 검증하기 위하여 이동물체의 이동 실시간이 가능한 시스템을 구축하였고, 다양한 배경을 포함한 실험영상 120 프레임을 처리한 결과 $89\%$ 이상의 추적 성공률을 보여주었다.

• ETRI Journal
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• 제34권3호
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• pp.399-409
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• 2012

In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (B)
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• pp.388-390
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• 2006

This paper presents an object tracking with radical change of color. Conventional Mean Shift do not provide appropriate result when major color distribution disappear. Our tracking approach is based on Mean Shift as basic tracking method. However we propose tracking algorithm that shows good results for an object of radical variation. The key idea is iterative update previous color information of an object that shows different color by using EM algorithm. As experiment results, we show that our proposed algorithm is an effective approach in tracking for a real object include an object having radical change of color.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.510-513
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• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.304-306
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• 2007

Methods of Object recognition from camera image are to compare features of color. edge or pattern with model in a general way. SIFT(scale-invariant feature transform) has good performance but that has high complexity of computation. Using simple color histogram has low complexity. but low performance. In this paper we represent a model as a color cooccurrence histogram. and we improve performance using pyramid matching. The color cooccurrence histogram keeps track of the number of pairs of certain colored pixels that occur at certain separation distances in image space. The color cooccurrence histogram adds geometric information to the normal color histogram. We suggest object recognition by pyramid matching of color cooccurrence histogram.

• 대한의용생체공학회:의공학회지
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• 제11권1호
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• pp.65-70
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• 1990

The phenomenon of color sensory has been mainly studied on the relation with the stimulus source of light source color according to dispersed energy of light. However, it has not been definitely found that the phenomenon of color sensory be collcerned with evoked potentials stimulated by object color. This paper proposes the method that evoked potentials stimulated by object colors are analyzed and examined on the phenomemon of color sensory. The model of evoked potentials is assumed that it is consisted of an additive noise and a transient signal caused by stimulus. The method which is used to estimate the signal is time-varying filtering.