• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.8-17
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• 2015

This paper presents a sound into color signal conversion using a colored-hearing synesthesia. The aim of the present paper is to implement a real-time conversion system which focuses on both hearing and sight which account for a great part of bodily senses. The proposed method of the real-time conversion of color into sound, in this paper, was simple and intuitive where scale, octave and velocity were extracted from MIDI input signals, which were converted into hue, intensity and saturation, respectively, as basic elements of HSI color model. In experiments, we implemented both the hardware system for delivering MIDI signals to PC and the VC++ based software system for monitoring both input and output signals, so we made certain that the conversion was correctly performed by the proposed method.

• 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.

• MALSORI
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• no.45
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• pp.63-77
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• 2003

The purpose of voice color conversion is to change the speaker identity perceived from the speech signal. In this paper, we propose a new voice color conversion algorithm through the formant shifting and the spectrum-tilt modification in the frequency domain. The basic idea of this technique is to convert the positions of source formants into those of target speaker's formants through interpolation and decimation and to modify the spectrum-tilt by utilizing the information of both speakers' spectrum envelops. The LPC spectrum is adopted to evaluate the position of formant and the information of spectrum-tilt. Our algorithm enables us to convert the speaker identity rather successfully while maintaining good speech quality, since it modifies speech waveforms directly in the frequency domain.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.25-27
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• 2009

This paper presents the stereoscopic conversion of flame images. The stereoscopic conversion is a technology that generates left and right images from a monoscopic image. Even though many conversion methods have been introduced and commercialized so far, the processing of flame images is relatively few. Such conventional methods are effectively used either real-time or off-line. However, the application of such schemes to special-effect images such as flame is hard to be applied. The proposed method is designed to convert a flame image into a stereoscopic image. Depth map of flame regions are produced based on the analysis of color models of flames. Experimental results tested on diverse flame image sets validates the effectiveness of the proposed method.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.231-238
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• 2012

This study aims for building an application system of converting sound into color image based on synesthetic perception. As the major features of input sound, both scale and octave elements extracted from F0(fundamental frequency) were converted into both hue and intensity elements of HSI color model, respectively. In this paper, we used the fixed saturation value as 0.5. On the basis of color model conversion theory, the HSI color model was then converted into the RGB model, so that a color image of the BMP format was finally created. In experiments, the basic system was implemented on both software and hardware(TMS320C6713 DSP) platforms based on the proposed sound-color image conversion method. The results revealed that diverse color images with different hues and intensities were created depending on scales and octaves extracted from the F0 of input sound signals. The outputs on the hardware platform were also identical to those on the software platform.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.290-303
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• 2010

Recently, researches to improve a quality and a color of a display are being actively studied because of the prosperous growth of the flat panel displays such as LCD, PDP and OLED. Automatically adjusting color temperatures based on user preferences is the one of the researches to provide the optimum display color. In this paper, along with defining the problems of prior methods, the user preferences against the priori defined ranges proposed by the MPEG-7 color temperature descriptor are inspected. Based on the analysis of user preferences, an optimal color temperature conversion curve is proposed. As a result of an analysis by ANOVA, tendencies of the user preferences against each range are proven to be similar to the prior research results. The repetition of the color temperature conversion against an image is not statistically significant.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.101-107
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• 2012

This study describes a proposed method of converting an input sound signal into a color image by emulating human synesthetic skills which make it possible to associate an sound source with a specific color image. As a first step of sound-to-image conversion, features such as fundamental frequency(F0) and energy are extracted from an input sound source. Then, a musical scale and an octave can be calculated from F0 signals, so that scale, energy and octave can be converted into three elements of HSI model such hue, saturation and intensity, respectively. Finally, a color image with the BMP file format is created as an output of the process of the HSI-to-RGB conversion. We built a basic system on the basis of the proposed method using a standard C-programming. The simulation results revealed that output color images with the BMP file format created from input sound sources have diverse hues corresponding to the change of the F0 signals, where the hue elements have different intensities depending on octaves with the minimum frequency of 20Hz. Furthermore, output images also have various levels of chroma(or saturation) which is directly converted from the energy.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.251-256
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• 2010

This paper aims for developing the intelligent robot emulating human synesthetic skills which associate a color image with sound, so that we are able to build an application system based on the principle of mutual conversion between color image and sound. As the first step, in this study, we have tried to realize a basic system using the color image to sound conversion. This study describes a new conversion method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. In addition, we present the method of converting color image into sound using color model conversion as well as histograms in the converted color model. In the basis of the method proposed in this study, we built a basic system using Microsoft Visual C++(ver. 6.0). The simulation results revealed that the hue, saturation and intensity elements of a input color image were converted into F0, harmonic and octave elements of a sound, respectively. The converted sound elements were synthesized to generate a sound source with WAV file format using Csound toolkit.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.642-649
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• 2016

This paper presents a method for conversion of muscular sense into both visual and auditory senses based on synesthetic perception. Muscular sense can be defined by rotation angles, direction changes and motion degrees of human body. Synesthetic interconversion can be made by learning, so that it can be possible to create intentional synesthetic phenomena. In this paper, the muscular sense was converted into both color and sound signals which comprise the great majority of synesthetic phenomena. The measurement of muscular sense was performed by using the AHRS(attitude heading reference system). Roll, yaw and pitch signals of the AHRS were converted into three basic elements of color as well as sound, respectively. The proposed method was finally applied to a wearable device, Samsung gear S, successfully.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.997-998
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• 2008

In this paper, we proposed a reduced memory overdrive architecture. Proposed overdrive architecture consists of 2D-DWT filter, BLI and Color Conversion block. For Frame Memory reduction we eliminated HH data in DWT-IDWT process and converted color space RGB into YCbCr. Consequently, we reduced Frame Memory about 50%.