• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.954-964
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• 2020

In immersive media, the most important factor that provides immersion is depth information. Therefore, it is essential to obtain high quality depth information in order to produce high quality immersive media. In this paper we propose an algorithm to improve depth map, considering the segmentation of images and the relationship between multiple views in multi-view systems. The proposed algorithm uses a super-pixel segmentation technique to divide the depth map of the reference view into several segments, and project each segment into adjacent view. Subsequently, the depth map of the adjacent view is improved using plane estimation using the information of the projected segment, and then reversed to the reference view. This process is repeated for several adjacent views to improve the reference depth map by updating the values of the improved adjacent views and the initial depth map of the reference view. Through simulation, the proposed algorithm is shown to surpass the conventional algorithm subjectively and objectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.249-254
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• 2013

In the area of computer vision, face recognition is being intensively researched. It is generally known that before a face is recognized it must be localized. Skin-color information is an important feature to segment skin-color regions. To extract skin-color regions the skin-color model based on multi-layer perceptron has been proposed. Extracted regions are analyzed to emphasize ellipsoidal regions. The results from this study show good accuracy for our vehicle driver face detection system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.148-153
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• 2009

Few methods have dealt with segmenting multiple images with analogous content. Concurrent images of a scene and gathered images of a similar foreground are examples of these images, which we term consistent scene images. In this paper, we present a method to segment these images based on manual segmentation of one image, by iteratively propagating information via multi-level cues with adaptive confidence. The cues are classified as low-, mid-, and high- levels based on whether they pertain to pixels, patches, and shapes. Propagated cues are used to compute potentials in an MRF framework, and segmentation is done by energy minimization. Through this process, the proposed method attempts to maximize the amount of extracted information and maximize the consistency of segmentation. We demonstrate the effectiveness of the proposed method on several sets of consistent scene images and provide a comparison with results based only on mid-level cues [1].

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.94-96
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• 2006

뮤직 비디오란 주어진 음악과 비디오가 동기화 된 형태의 창작물을 뜻한다. 기존의 뮤직비디오 제작방식에서는 만들어진 음악을 위해 영상 촬영에 전문적인 촬영 기술을 요구하였다. 본 논문에선 보다 쉬운 뮤직비디오 생성을 위하여 비디오와 음악의 특성을 분석하여 자동적인 뮤직비디오 생성시스템을 소개한다. 두 개체의 연속성을 보장하는 비교를 위해 우리는 각각의 객체의 흐름을 분석하고, 흐름의 유사성을 기준으로 분할하는 기법을 제시한다. 분할된 영상과 음악의 특성 비교를 통한 최적화된 매칭기법 을 비롯하여 보다 다양한 조각 생성을 위한 다중 레벨(multi-level)분할 기반의 매칭 기법을 소개한다. 본 논문의 기술을 사용하여, 일반인이 홈비디오 등을 사용하여 손쉽게 뮤직비디오를 제작할 수 있다.

• Convergence Security Journal
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• v.8 no.2
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• pp.95-102
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• 2008

In this paper, we proposed topology aggregation method that efficiently aggregating topology information in simple node topology. And, it improved QoS of networks by improving call success rate and call access time. Proposed method can improving performance of network by decreasing aggregation information and aggregating multi-links information between boundary nodes using the line segment scheme within bandwidth and delay parameter. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme in respect to call success rate, access time.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.2
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• pp.217-224
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• 2005

A new roof edge detection method based on multi level scales of wavelet function is proposed in this paper roof edge and its direction are obtained in this new methods at one time. Besides. scale characteristics of detecting roof edge is analyzed. And a few new methods on fingerprint image pre-processing are described. A method segmenting foreground/background of fingerprint images is proposed, in which Prior estimation of direction field is not required any more. A segmentation method based on multi-scale roof edges is implemented. and the valid scale range of the method is defined. too. And the method is used to segment ridges and valleys in fingerprint images simultaneously The exact direction fields made up of the direction of each point in ridges can be obtained when detecting ridges exactly based on the roof edge detector, in comparison with the traditional coarse estimation of direction fields. Obviously. it will establish a solid foundation for the sequent fingerprint identification.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.3
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• pp.448-462
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• 1995

The purpose of this study was on the development of jeans via conjoint analysis and marketing strategies for each segmented market. The questionnaire was composed vervel card and defining the proper marketing strategies for each segmented market. The 269 usable data was distributed to the Univ student and carrier women through multi- stage , ;ambling. The statistical results were processed by the SPSS, PC MDS, and MANZANOLA program. The used methods of statistical data were conjoint analysis, KYST, PROFIT, factor analysis, frequency, one-way ANOVA, SNK, and paired t-test. The results of this study can be summaries as follows: 1. In competitor analysis, Korean brands were in low price zone, but foreign in high price and character style zone. 2. There was significant differences Korean brands and foreign brands on evaluating. On the basis of the perceptual maps, most of Korean brands were evaluated as having a good price and most of foreign brands were evaluated as having a good design. 3. The optimal jeans has the well-known brand, the price of less than 30, 000 won, traditional style, and good quality. In four attributes of clothing buying process, brand is most important attribute of jeans. Segment market 1.All the jeans that they have is Korean brand. Income, amount spent per month on clothing, how many having jeans is low market. Self-centered factor is lowest. In the clothing sari ales lifestyle, they considered most conviniance. Segment market 2-They have one foreign brand jeans. Income, amount spent per month on clothing, how many having jeans is low market. Self-centered factor is lowest Segment market 3-They have two foreign brand jeans. Income, amount spent pet month on clothing, how many having jeans is high market. Self-centered factor is high. In the clothing variables lifestyle, they considered brand, continuance, and character. Segment market 4-They have more than three foreign brand. Income amount spent per month on clothing, and how many having jeans is high market. Self-centered factor is high. In the clothing variables lifestyle, they considered most brand, and character.

• Journal of Sasang Constitutional Medicine
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• v.18 no.3
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• pp.64-74
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• 2006

1. Objectives and Methods A Study on the Characteristics of the Korean Adult Male Sound according to Sasang Constitution using PSSC with a Sentence. Sasang Constitutional Medicine(SCM) is the one of the traditional Korean Medicine. It classifies people into four categories like Taeyangin, Soyangin, Taeumin and Soeumin. The rule to classify is Appearance and Body Shape, Facial Appearance and Speech, Character and Talents and Diseases and Medications. This study was done to investigate the relationships between Voice and Sound parameters using PSSC(Phonetic System of Sasang Constitution) in a sentence. Experimental Participants were 195 Korean adult males including 1 Taeyangin, 37 Soyangin, 105 Taeumin and 52 Soeumin. Sasang Constitutional specialist used PSSC and Korean Medical Diagnosis to classify participants into four constitution. 2. Results In Pitch segment, Soyangin's Center freq.(4) was significantly high compared with Taeyangin and Taeumin groups. Soyangin's and Soeumin's Center freq.(6) was significantly high compared with Taeyangin and Taeumin groups. In APQ segment and Octave segment, there were no significant differences among four groups. In Shimmer segment, Taeumin's F Shimmer(1) and F Shimmer(2) were significantly high compared with Taeyangin and Soyangin groups. In Energy segment, Taeyangin's 2k-4k total sum, 2k-4k dev., C dev., C# dev. and D S.D. were significantly high compared with other groups. In Recording time segment, there was no significant difference among four groups. More Taeyangin cases and the other parameters are needed to determine constitution using PSSC and to make PSSC effective. 3. Conclusions From above result, there is the possibility of efficiency standard guide for constitution diagnosis by analyzation og voice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.347-370
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• 2019

In the computer-aided detection (CAD) system of pulmonary nodules, a high false positive rate is common because the density and the computed tomography (CT) values of the vessel and the nodule in the CT images are similar, which affects the detection accuracy of pulmonary nodules. In this paper, a method of automatic detection of pulmonary nodules based on multi-scale enhancement filters and 3D shape features is proposed. The method uses an iterative threshold and a region growing algorithm to segment lung parenchyma. Two types of multi-scale enhancement filters are constructed to enhance the images of nodules and blood vessels in 3D lung images, and most of the blood vessel images in the nodular images are removed to obtain a suspected nodule image. An 18 neighborhood region growing algorithm is then used to extract the lung nodules. A new pulmonary nodules feature descriptor is proposed, and the features of the suspected nodules are extracted. A support vector machine (SVM) classifier is used to classify the pulmonary nodules. The experimental results show that our method can effectively detect pulmonary nodules and reduce false positive rates, and the feature descriptor proposed in this paper is valid which can be used to distinguish between nodules and blood vessels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1888-1906
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• 2024

Aiming at the problems that the edge of melanoma image is fuzzy, the contrast with the background is low, and the hair occlusion makes it difficult to segment accurately, this paper proposes a model MSCNet for melanoma segmentation based on U-net frame. Firstly, a multi-scale pyramid fusion module is designed to reconstruct the skip connection and transmit global information to the decoder. Secondly, the contextural information conduction module is innovatively added to the top of the encoder. The module provides different receptive fields for the segmented target by using the hole convolution with different expansion rates, so as to better fuse multi-scale contextural information. In addition, in order to suppress redundant information in the input image and pay more attention to melanoma feature information, global channel attention mechanism is introduced into the decoder. Finally, In order to solve the problem of lesion class imbalance, this paper uses a combined loss function. The algorithm of this paper is verified on ISIC 2017 and ISIC 2018 public datasets. The experimental results indicate that the proposed algorithm has better accuracy for melanoma segmentation compared with other CNN-based image segmentation algorithms.