• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.1-11
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• 1999

surface texture denotes set of tiny repetitive geometric features on an object surface. 3D Printing can readily create a surface of controlled macro-textures of high geometric complexity. Designing surface textures for 3D Printing, however, is difficult due to complex macro-structure of the tiny texture geometry since it needs to be compatible with the non-traditioal manufacturing method. In this paper we propose a visual simulation technique involving development of a virtual model-an intermediate geometric model-of the surface texture design prior to fabricating the physical model. Careful examination of the virtual model before the actual fabrication can help minimize unwanted design iterations. The proposed technique demonstrated visualization capability by comparing the virtual model with the physical model for several test cases.

• Food Engineering Progress
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• v.21 no.4
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• pp.303-311
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• 2017

To automate cooking processes, quantitative descriptions are needed on how quality parameters, such as texture change during heating. Understanding mechanical property changes in foods during thermal treatment due to changes in chemical composition or physical structure is important in the context of engineering models and in precise control of quality in general. Texture degradation of food materials has been studied widely and softening kinetic parameters have been reported in many studies. For a better understanding of kinetic parameters, applied kinetic models were investigated, then rate constants at $100^{\circ}C$ and activation energy from previous kinetic studies were compared. The food materials are hardly classified into similar softening kinetics. The range of parameters is wide regardless of food types due to the complexity of food material, different testing methods, sample size, and geometry. Kinetic parameters are essential for optimal process design. For broad and reliable applications, kinetic parameters should be generated by a more consistent manner so that those of foods could be compared or grouped.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.441-449
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• 2007

In clustering for image segmentation, large amount of computation and typical segmentation errors have been important problems. In the paper, we suggest a new method for minimizing these problems. Markers in marker-controlled watershed transform represent segmented areas because they are starting-points of extending areas. Thus, clustering restricted by marker pixels can reduce computational complexity. In our proposed method, the markers are selected by Gabor texture energy, and cluster information of them are generated by FCM (fuzzy c-mean) clustering. Generated areas from watershed transform are merged by using cluster information of markers. In the test of Brodatz' texture images, we improved typical partition-errors obviously and obtained less computational complexity compared with previous FCM clustering algorithms. Overall, it also took regular computational time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.4
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• pp.205-211
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• 2014

This paper addresses the framework of object-oriented image coding, describing a new algorithm, based on monodimensional Legendre polynomials, for texture approximation. Through the use of 1D orthogonal basis functions, the computational complexity which usually makes prohibitive most of 2D region-oriented approaches is significantly reduced, while only a slight increment of distortion is introduced. In the aim of preserving the bidimensional intersample correlation of the texture information as much as possible, suitable pseudo-bidimensional basis functions have been used, yielding significant improvements with respect to the straightforward 1D approach. The algorithm has been experimented for coding still images as well as motion compensated sequences, showing interesting possibilities of application for very low bitrate video coding.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.114-127
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• 2017

This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test color images reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.1
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• pp.11-18
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• 1999

The objective of this study are to figure out the physical attributes of the three predictors in the Informational Approach: complexity, coherence, mystery and to investigate the relationships between these attributes and the preference exploratively. Visual inspection of the scenes relative to their rated levels of the predictors revealed the existence of relationship between these variables and the physical attributes. The following are the summary of the relationship between three predictors and the physical attributes: (1) The level of complexity was associated with the pattern of physical attributes which were the amount of facility, line, shape, color plant and arrangement of the visual elements. (2) The level of coherence was related with the regular arrangement of the visual elements. For example, there was certain pattern founded the color, shape, texture was applied to the various space repetitively and symmetrically. (3) The level of mystery had the relationship with the physical attributes of screen, spatial definition, distance of view, physical accessibility, radiant forest, the depth of space.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.718-727
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• 2015

In this paper, we present a novel segmentation method that can extract new foreground objects from a current frame in real-time. It is performed by detecting differences between the current frame and reference frame taken from a fixed camera. We minimize computing complexity for real-time video processing. First DCT (Discrete Cosine Transform) is utilized to generate rough binary segmentation maps where foreground and background regions are separated. DCT shows better result of texture analysis than previous methods where texture analysis is performed in spatial domain. It is because texture analysis in frequency domain is easier than that in special domain and intensity and texture in DCT are taken into account at the same time. We maximize run-time efficiency of DCT by considering color information to analyze object region prior to DCT process. Last we use Guided filter for natural matting of the generated binary segmentation map. In general, Guided filter can enhance quality of intermediate result by incorporating guidance information. However, it shows some limitations in homogeneous area. Therefore, we present an additional method which can overcome them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.11-21
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• 2008

In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1369-1373
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• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.