• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.

• Journal of Mushroom
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• v.10 no.1
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• pp.37-43
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• 2012

This study was carried to identify a correct species and asses genetic diversity within the same species of Polyporus spp. preserved in Division of applied Microbiology. Contaminated isolates showed different growth rates, morphology and color of hyphae. We have reconstructed the phylogenetic tree of a select group of Polyporus spp. using nucleotide sequences of the internal transcribed spacer region(ITS) region. The phylogenetic tree was constructed by using the neighbor-joining method. PELF primers of 20-mer were used to assess genetic diversity of preserved isolates. Sequence analysis showed that three strains were different species and four strains were identified completely different nomenclature. According to the analysis of ITS sequences, the genus Polyporus clustered into five distinct group, most of which correlated with species-groups identified by RAPD method. Four isolates included strain PM02 showed high similarity with P. arcularius, four isolates included strain PM03 high similarity with P. alveolaris, three isolates included strain PM01 high similarity with P. tuberaster, and PM 06 and PM04 high similarity with P. brumalis and P. squamossus. Isolates were collected in the United States(PM10, PM11) was identified as P. alveolarius and P. arcularius. RAPD analysis of genetic polymorphisms of genus Polyporus showed a very different band patterns. As the result of RAPD and ITS region sequences analysis for preserved isolates, it seems likely that 6 isolates of Polyporus spp. may be need to reclassify or eliminate from preserved catalogue.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.214-223
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• 2024

The recent increase in maritime traffic and coastal leisure activities has led to a rise in various marine accidents. These incidents not only result in damage to human life and property but also pose a significant risk of marine pollution involving oil and hazardous and noxious substances (HNS) spills. Therefore, effective ship monitoring is crucial for preparing and for responding to marine accidents. This study conducted an aerial experiment utilizing hyperspectral remote sensing to develop a maritime ship monitoring system. Hyperspectral aerial measurements were carried out around Gungpyeong Port in the western coastal region of the Korean Peninsula, and spectral libraries were constructed for various ship decks. The spectral correlation similarity (SCS) technique was employed for ship detection, analyzing the spatial similarity distribution between hyperspectral images and ship spectra. As a result, 15 ships were detected in the hyperspectral images. The color of each ship's deck was classified based on the highest spectral similarity. The detected ships were verified by matching them with high-resolution digital mapping camera (DMC) images. This foundational study on the application of aerial hyperspectral sensors for maritime ship detection demonstrates their potential role in future remote sensing-based ship monitoring systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.61-66
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• 2010

The purpose of this experiment is to analyze the basic status of brain. Which are consist of rest, attention and concentration, of the brain by measuring the temperature of color by changing RGB color after manufacturing LED-illumination stand. Basic status (rest, attention and concentration) of experimenter were measured temperature of colors having three difference temperature like as $2,300^{\circ}K$, $4,000^{\circ}K$ and $6,000^{\circ}K$. The results was shown that experimenter feels more comfortable and relaxation by decreasing the temperature of color. For example we can see the little increase of concentration index at $4,000^{\circ}K$ condition and we can estimate that right brain can be more activated at the $4,000^{\circ}K$ condition. But we can not find out any different at the $6,000^{\circ}K$ condition. Main cause of no difference from the color temperature was the similarity of color temperature under the general fluorescent lamp. And interface temperature of radiant heat design results LED and PCB was approximately 80 degrees to COMSOL Multiphysics, and changed until approximately 50 degrees until a floor plane of PCB, and verification as arranged chip LED to metal PCB, and it was possible, and a near radiant heat design was confirmed to an approximate value of, as a result, acid manufacture.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.375-378
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• 2000

In this paper, we propose a novo] content-based image retrieval system using both Hidden Markov Model(HMM) and an improved chain code. The Gaussian Mixture Model(GMM) is applied to statistically model a color information of the image, and Deterministic Annealing EM(DAEM) algorithm is employed to estimate the parameters of GMM. This result is used to segment the given image. We use an improved chain code, which is invariant to rotation, translation and scale, to extract the feature vectors of the shape for each image in the database. These are stored together in the database with each HMM whose parameters (A, B, $\pi$) are estimated by Baum-Welch algorithm. With respect to feature vector obtained in the same way from the query image, a occurring probability of each image is computed by using the forward algorithm of HMM. We use these probabilities for the image retrieval and present the highest similarity images based on these probabilities.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.75-82
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• 2002

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper Propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with χ2 histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.127-135
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• 2009

This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.

• Journal of Applied Biological Chemistry
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• v.50 no.4
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• pp.221-226
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• 2007

The high molecular-weight mucilage extracted and purified from cactus fruit of Opuntia ficus-indica var. Saboten was degraded by the cell-free culture filtrate of a fungus isolated from soil. TLC analysis of the polymeric mucilage after incubation with the fungal culture filtrate confirmed its degradation. When the degradation products were tested for their qualitative reactions with ninhydrin and phenol-sulfuric acid, only phenol-sulfuric acid gave positive development, and ninhydrin did not show any observable color reaction. This coloring reaction suggested the presence of a carbohydrate without an amino group within the mucilage. Analyses by HPLC and liquid gel permeation chromatography on sephadex G-100 also provided additional information on degradation of the mucilage by the fungal culture filtrate. The sequences of ITS-5.8S rDNA from the fungal isolate that was cultivated for the preparation of mucilage-degrading enzyme showed 99% similarity to those of Pestalotiopsis aquatica.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.156-165
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• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.373-374
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• 2009

이 논문에서는 이미지간의 유사도를 측정하기 위하여 컬러 특징값을 추출하는 한 방법을 제시하고자 한다. 컬러특징값은 다양한 형태로 추출될 수 있지만 자연적인 조명 환경하에서 어느 정도 invariance consistency 특징을 유지하는 방법을 찾아내는 것이 중요하다. 컬러 coocurrence 특징값은 많은 연구가 진행되어 여러 응용에서 적용되고 있지만 여기서는 컬러의 invariance 공간에 대한 coocurrence 특징값을 추출하여 이미지 유사도를 측정하는 방식을 제시하고자 한다.