• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.330-335
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• 2004

In this paper, we propose the technique for recognizing the human emotion by using the color image. To do so, we first extract the skin color region from the color image by using HSI model. Second, we extract the face region from the color image by using Eigenface technique. Third, we find the man's feature points(eyebrows, eye, nose, mouse) from the face image and make the fuzzy model for recognizing the human emotions (surprise, anger, happiness, sadness) from the structural correlation of man's feature points. And then, we infer the human emotion from the fuzzy model. Finally, we have proven the effectiveness of the proposed method through the experimentation.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.291-298
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• 2009

In this paper we proposed a vision based realtime hand gesture recognition method. To extract skin color, we translate RGB color space into YCbCr color space and use CbCr color for the final extraction. To find the center of extracted hand region we apply practical center point extraction algorithm. We use Kalman filter to tracking hand region and use HMM(Hidden Markov Model) algorithm (learning 6 type of hand gesture image) to recognize it. We demonstrated the effectiveness of our algorithm by some experiments.

• Cartoon and Animation Studies
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• s.39
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• pp.393-412
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• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.710-715
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• 2003

In this paper, we propose the new emotion recognition method for intelligently recognizing the human's emotion using the template vector and neural network. In the proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). The proposed method is based on the template vector extraction and the template location recognition by using the color difference. It is not easy to extract the skin color area correctly using the single color space. To solve this problem, we propose the extraction method using the various color spaces and using the each template vectors. And then we apply the back-propagation algorithm by using the template vectors among the feature points). Finally, we show the practical application possibility of the proposed method.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.336-344
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• 2012

As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.65-72
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• 2006

The traffic lights detection and recognition system is an essential module of the driver warning and assistance system. A method which is a color vision-based real time detection and recognition of traffic lights is presented in this paper This method has four main modules : traffic signals lights detection module, traffic lights boundary candidate determination module, boundary detection module and recognition module. In traffic signals lights detection module and boundary detection module, the color thresholding and the subtraction value of saturation and intensity in HSI color space and detection probability mask for lights detection are used to segment the image. In traffic lights boundary candidate determination module, the detection mask of traffic lights boundary is proposed. For the recognition module, the AND operator is applied to the results of two detection modules. The input data for this method is the color image sequence taken from a moving vehicle by a color video camera. The recorded image data was transformed by zooming function of the camera. And traffic lights detection and recognition experimental results was presented in this zoomed image sequence.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.11-20
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• 2022

Currently, the black-white QR (Quick Response) codes have been used widely in consumer advertising fields and the study of color QR codes have received a growing demand because of much higher data encoding capacity. Color QR codes can be reproduced by the printing and scanning processes, however, these encounter colors distortion caused by insufficient lighting, low resolution of camera and geometric deformation during the capturing processes. In order to overcome these problems, this paper proposes an efficient decoding algorithm for color QR codes with inserted patterns, which are dealt with conventional studies. These are evaluated in view of the recognition rate under different noise conditions, for example, Gaussian noises/blurring and geometric deformation. Experimental results demonstrate that the color QR codes with simple pattern can resist the distortion of Gaussian noises/blurrings.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.257-262
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• 2009

A method of the region extraction and recognition of a speed sign in the real road environment is proposed. The region of speed sign is extracted by using color information and then numbers are segmented in the region. We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. In image sequences of the real road environment, a robust recognition results are achieved with speed signs at normal condition as well as inclined.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.216-221
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• 2003

Emotions recognition is a topic on which little research has been done to date. This paper proposes a new method that can recognize the human s emotion from facial image by using eigenspace. To do so, first, we get the face image by using the skin color from the original color image acquired by CCD color camera. Second, we get the vector image which is projected the obtained face image into eigenspace. And then, we propose the method for finding out each person s identification and emotion from the weight of vector image. Finally, we show the practical application possibility of the proposed method through the experiment.