• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.142-148
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• 2011

The final aim of the present study is to develop the intelligent robot, emulating human synesthetic skills which make it possible to associate a color image with a specific sound. This can be done on the basis of the mutual conversion between color image and sound. As a first step of the final goal, this study focused on a basic system using a conversion of color image into sound. This study describes a proposed method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. The method of converting color image into sound was implemented by using HSI histograms through RGB-to-HSI color model conversion, which was done by Microsoft Visual C++ (ver. 6.0). Two different color images were used on the simulation experiments, and the results revealed that the hue, saturation and intensity elements of each input color image were converted into fundamental frequency, harmonic and octave elements of a sound, respectively. Through the proposed system, the converted sound elements were then synthesized to automatically generate a sound source with wav file format, using Csound.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.187-194
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• 2013

The final aim of the present study is to build a system of converting a color image into musical elements based on a synesthetic perception, emulating human synesthetic skills, which make it possible to associate a color image with a specific sound. This can be done on the basis of the similarities between physical frequency information of both light and sound. As a first step, an input true color image is converted into hue, saturation, and intensity domains based on a color model conversion theory. In the next step, musical elements including note, octave, loudness, and duration are extracted from each domain of the HSI color model. A fundamental frequency (F0) is then extracted from both hue and intensity histograms. The loudness and duration are extracted from both intensity and saturation histograms, respectively. In experiments, the proposed system on the conversion of a color image into musical elements was implemented using standard C and Microsoft Visual C++(ver. 6.0). Through the proposed system, the extracted musical elements were synthesized to finally generate a sound source in a WAV file format. The simulation results revealed that the musical elements, which were extracted from an input RGB color image, reflected in its output sound signals.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.529-537
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• 2011

In this paper, we propose a stable scale adaptive tracking method that uses centroids of the target colors. Most scale adaptive tracking methods have utilized histograms to determine target window sizes. However, in certain cases, histograms fail to provide good estimates of target sizes, for example, in the case of occlusion or the appearance of colors in the background that are similar to the target colors. This is due to the fact that histograms are related to the numbers of pixels that correspond to the target colors. Therefore, we propose the use of centroids that correspond to the target colors in the scale adaptation algorithm, since centroids are less sensitive to changes in the number of pixels that correspond to the target colors. Due to the spatial information inherent in centroids, a direct relationship can be established between centroids and the scale of target regions. Generally, after the zooming factors that correspond to all the target colors are calculated, the unreliable zooming factors are filtered out to produce a reliable zooming factor that determines the new scale of the target. Combined with the centroid based tracking algorithm, the proposed scale adaptation method results in a stable scale adaptive tracking algorithm. It tracks objects in a stable way, even when the background colors are similar to the colors of the object.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.149-154
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• 2001

멀티미디어 정보표현 기술인 MPEG-7 표준이 빠른 속도의 진전을 보임에 따라 이를 활용한 검색 기술 개발도 활발히 진행 중에 있다 방대한 량의 동영상 내용 검색 기술 연구에 있어서 우선적으로 고려되어야 할 부분이 내용이 연속되는 프레임들의 분류이다. 이를 위해서는 물리적인 장면전환이 이루어지는 부분에 대한 실시간 자동 cut detection 기술 및 이 컷 프레임 영상에 대한 내용 기술을 자동적으로 수행할 필요성이 있다. 각 컷 프레임의 자동 내용 기술의 전처리로써 본 논문에서는 장면전환이 생기는 프레임의 영상의 어떠한 정보도 사전 정보로 취하지 않고 사용자의 개입이 없는 상황에서 영상의 컬러 특성 및 에지 정보만을 가지고 shape 영역 segmentation을 자동으로 실행하는 방법을 제안한다. 제안한 방법의 성능은 segmentation된 영상과 원 영상과의 영역비교를 통한 유사도에 의해 평가하며, 시뮬레이션 결과에서 제안한 알고리즘은 평균 90%이상의 영역 분할이 정확하게 됨을 알 수 있었고, 컬러의 구분이 명확하지 않은 자연영상에서도 robust한 segmentation 결과를 나타냄을 본 연구를 통하여 알 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.3
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• pp.8-12
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• 1999

Edge detection is a key component for many modern computer vision applications. While it is certainly not the only way to identify an object, or track a feature, it can be one of the most convenient if it is done quickly and consistently. Many algorithms proposed is applied to gray level images. But. there are limits in method using only intensity information, so, many researchers has try to done research about using color information. In this paper, we propose the new edge detection method usign color information, implement the widely used algorithms and compared with them in performance. In result of experiment, we show that the proposed algorithm have better result in fine detail and shaded region of image.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.207-214
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• 2010

A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.163-165
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• 2011

In this paper we collect data concerning sleep environments in a bedroom and analyze the relationship between the collected condition data and sleep. In addition, this paper detects scene changes from the subjects in a sleeping state and presents the physical conditions, reactions during sleep, and physical sensations and stimuli. To detect scene changes in image sequences, we used color histogram for the difference between the preceding frame and the current frame. In addition, to extract the tossing and turning for different situations, the subjects were instructed to enter the level of fatigue, the level of drinking, and the level of stomach emptiness.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.13-19
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• 2003

There are active researches on automated guided vehicles(AGV) generally used in flexible manufacturing system(FMS) or automated warehouse systems(AWS). Because existing AGV uses magnetic tapes, electric wire, RF or laser as guidelines, its installation and modification require a lot of money and time. The present study implemented AGV that detects paths marked with 50mm Yellow tape using a mono-color CCD camera. Because it uses color tape, it is easy and inexpensive to install and change lines. This study presented the structure of the developed AGV, the image Processing technique for detecting guidelines by ing the characteristics of color, and the result of operating AGV.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.19-23
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• 2013

TIn this paper, we propose a novel fuzzy stretching method that adopts a triangle type fuzzy membership function to control the highest and lowest brightness limit dynamically. As an essential procedure to enhance the brightness contrast, stretching is an important procedure in color image processing. While popular Ends-in Search stretching method should be provided fixed minimum and maximum brightness threshold from experience, our proposed method determines them dynamically by fuzzy membership functions. The minimum and maximum limit is determined by computing the lowest and highest pixel value according to the membership degree of our designed triangle type membership function. The experiment shows that the proposed method result in far less skewed histogram than those of Ends-in Search stretching thus successfully verifies its effectiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.142-145
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• 2008

This paper proposes a computationally efficient algorithm for color image segmentation using self-organizing map(SOM) and grassfire algorithm. We reduce a computation time by decreasing the number of input neuron and input data which is used for learning at SOM. First converting input image to CIE $L^*u^*v^*$ color space and run the learning stage with the SOM-input neuron size is three and output neuron structure is 4by4 or 5by5. After learning, compute output value correspondent with input pixel and merge adjacent pixels which have same output value into segment using grassfire algorithm. The experimental results with various images show that proposed method lead to a good segmentation results than others.