• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.19-27
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.319-326
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• 2004

In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.

• 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.

• Science of Emotion and Sensibility
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• v.10 no.4
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• pp.631-637
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• 2007

This research focuses on similarity evaluation of images according to tones of images. Color space of images were converted RGB color space into HSI color space. The information entropy criteria has been taken for evaluating similarity of images for digital library. The similarity was then calculated by combining correlation coefficients and information entropy. Those two values are further analyzed with a relation to human sensibility.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.173-178
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• 2014

In this study, the new color image processing algorithms with an android-based mobile device are developed to detect the abnormal color densities in a skin image and interpret them as the vitiligo lesions. Our proposed method is firstly based on transforming RGB data into HSI domain and segmenting the imag into the vitiligo-skin candidates by applying Otsu's threshold algorithm. The structure elements for morphological image processing are suggested to delete the spurious regions in vitiligo regions and the image blob labeling algorithm is applied to compare RGB color densities of the abnormal skin region with them of a region of interest. Our suggested color image processing algorithms are implemented with an android-platform smartphone and thus a mobile device can be utilized to diagnose or monitor the patient's skin conditions under the environments of pervasive healthcare services.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.623-626
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• 2003

Image analysis was performed with two color systems, Red-Green-Blue (RGB) values and normalized Hue-Saturation-Intensity (HSI). We conducted field studies in Cheongju to determine canopy spectral reflectance and digital image analysis of rice. Spectral reflectance measurements made with a portable spectrometer(LI-1800) correlated with growing stage and digital images for rice. Images in which the color was specified by the common RGB coordinates could be used when there was a sharp contrast between the color of the rice and that of the field soil. In the absence of sharp contrast, identification of the rice covered area was much easer after the color had been transformed into HSI coordinates. This study introduced fundamental theories in digital image analysis and applied that for field situations rice.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.450-460
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• 2005

Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.92-98
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• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.