• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.37-46
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• 2010

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.188-194
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• 2014

The feature extraction mechanism of the CASA(Computational Auditory Scene Analysis) system uses time continuity and frequency channel similarity to compose a correlogram of auditory elements. In segmentation, we compose a binary mask by using cross-correlation function, mask 1(speech) has the same periodicity and synchronization. However, when there is delay between autocorrelation signals with the same periodicity, it is determined as a speech, which is considered to be a drawback. In this paper, we proposed an algorithm to improve discrimination of channel similarity using Weighted Cross-correlation in segmentation. We conducted experiments to evaluate the speech segregation performance of the CASA system in background noise(siren, machine, white, car, crowd) environments by changing SNR 5dB and 0dB. In this paper, we compared the proposed algorithm to the conventional algorithm. The performance of the proposed algorithm has been improved as following: improvement of 2.75dB at SNR 5dB and 4.84dB at SNR 0dB for background noise environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.228-237
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• 2013

In this paper, we propose a normalized cross correlation(NCC)-based multiview background subtraction method which is robust when an object and background have similar color. When the background of the capturing environment is not artificially composed, the regions in the background images which would be occluded by an object tends to have difference colors. The colors of those regions, however, becomes similar when an object enters the capturing environment. Based on this assumption, this paper proposes a concept of GoNCC(Graph of Normalized Cross Correlation). GoNCC is the distribution of NCC between a pixel in an image and pixels related by epipolar constraints with the pixel. The proposed multiview background subtraction method is performed by comparing GoNCC of the current images with the background images. To reduce computational complexity, we perform multiview background subtraction only to the pixels undetermined by single view background subtraction. Experimental results show that the proposed method is more robust to color similarity between an object and background than a single-view background subtraction method and a previous multiview background subtraction method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.333-337
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• 2002

A content-based image retrieval method using color, texture, and shape features is proposed in this paper. A region segmentation technique using PIM(Picture Information Measure) entropy is used for similarity indexing. For segmentation, a color image is first transformed to a gray image and it is divided into n$\times$n non-overlapping blocks. Entropy using PIM is obtained from each block. Adequate variance to perform good segmentation of images in the database is obtained heuristically. As variance increases up to some bound, objects within the image can be easily segmented from the background. Therefore, variance is a good indication for adequate image segmentation. For high variance image, the image is segmented into two regions-high and low entropy regions. In high entropy region, hue-saturation-intensity and canny edge histograms are used for image similarity calculation. For image having lower variance is well represented by global texture information. Experiments show that the proposed method displayed similar images at the average of 4th rank for top-10 retrieval case.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1188-1193
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• 2013

In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• Journal of Animal Science and Technology
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• v.57 no.12
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• pp.44.1-44.9
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• 2015

Background: Heat shock proteins play an important role in protection from stress stimuli and metabolic insults in almost all organisms. Methods: In this study, computational tools were used to deeply analyse the physicochemical characteristics and, using homology modelling, reliably predict the tertiary structure of the blunt snout bream (Ma-) Hsp70 and Hsc70 proteins. Derived three-dimensional models were then used to predict the function of the proteins. Results: Previously published predictions regarding the protein length, molecular weight, theoretical isoelectric point and total number of positive and negative residues were corroborated. Among the new findings are: the extinction coefficient (33725/33350 and 35090/34840 - Ma-Hsp70/ Ma-Hsc70, respectively), instability index (33.68/35.56 - both stable), aliphatic index (83.44/80.23 - both very stable), half-life estimates (both relatively stable), grand average of hydropathicity (-0.431/-0.473 - both hydrophilic) and amino acid composition (alanine-lysine-glycine/glycine-lysine-aspartic acid were the most abundant, no disulphide bonds, the N-terminal of both proteins was methionine). Homology modelling was performed by SWISS-MODEL program and the proposed model was evaluated as highly reliable based on PROCHECK's Ramachandran plot, ERRAT, PROVE, Verify 3D, ProQ and ProSA analyses. Conclusions: The research revealed a high structural similarity to Hsp70 and Hsc70 proteins from several taxonomically distant animal species, corroborating a remarkably high level of evolutionary conservation among the members of this protein family. Functional annotation based on structural similarity provides a reliable additional indirect evidence for a high level of functional conservation of these two genes/proteins in blunt snout bream, but it is not sensitive enough to functionally distinguish the two isoforms.

• Journal of the Korea Fashion and Costume Design Association
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• v.13 no.4
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• pp.1-14
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• 2011

This study is to analyze the image similarity and the preference for clothing stores in the 6 giant discount chains in Daejeon. The survey for this study was based on the questionnaires accomplished by 257 people through the multidimensional scaling. The results are as follows First, 6 clothing stores had 4 image groups located in 4 coordinates. CW(Costco Wholesale), NH(Nonghyup Hanaro-Mart), and SZ(Save Zone) had a similar distinct image, while HP(Home Plus) and EM(E-Mart), and LM(Lotte-Malt) also had similar differentiated images. Second, according to the preference analysis in terms of demographic characteristic, NH had the lowest preference from the people of all the different ages, while SZ had the highest. HP, EM, CW, and LM had their own preference in the following order: in the thirties, forties, and over fifties. Meanwhile, relatively, SZ is preferred by the people in their twenties and people over age fifty liked CW more. Third, according to the analysis of the preference for clothing stores in the giant discount chains in terms of educational background, clothing consumers who had high school degrees preferred NH and LM, people with 2 year college degrees liked HP and EM more, while 4-year college graduates and people with higher education had preference for SZ. Finally, according to the preference analysis in terms of income level, higher income groups preferred SZ and CW and lower income groups liked LH and LM more, while HP and EM had high preference from all kinds of income groups.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.250-260
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• 2023

Background: Crabgrass (Digitaria ciliaris, Poaceae) is a globally distributed weed, including in Afro-Eurasia, America, and Australia. As a highly gregarious plant, crabgrass is an important habitat for a diverse array of insects, and a potential habitat for agricultural pests. To compare the insect communities associated with the crabgrass community, insects were sampled using sweep sampling (100 sweeps per sample) at five sites, including Daejeon (Daejeon and Gap rivers), Anseong, Namhae, and Inje, with a focus on the Daejeon River. Results: A total of 5,888 individual insects belonging to eight orders, 42 families, and 115 species were collected from the five sites. Both the number of species and individuals of Hemiptera were the highest at all of the sites. In the present study, 73% of the insect population fed on D. ciliaris as a host plant. The dominant species in the D. ciliaris community was Laodelphax striatellus (Delphacidae), being ubiquitous at all the sites which showed a high abundance of rice pests in the communities and the suitability of D. ciliaris as an alternative host plant for them. The Shannon-Wiener diversity index was highest in Inje on 17 September (2.88), and the Chao1-bc diversity index was highest in the Gap River on 5 September (80). The sampling efficiency of 100 sweep samples (sample coverage) was calculated to be as high as 90%. The results of the samples taken from September to November in the Daejeon River showed that the number of species and individuals decreased gradually over time, and the number of dominant species decreased sharply between September and October. Similarity analysis indicated that sampling dates that were closer together yielded sampled assemblages with higher faunal similarity. In addition, in each sampling, the difference in the minimum temperature during the two-week period prior to sampling and faunal similarities were negatively correlated. Conclusions: This study provides foundational data that could enhance our understanding of insect diversity in D. ciliaris. The data can facilitate ecological conservation and management of Korean grasslands generally, as well as identification of potential pests that may disperse from D. ciliaris communities to nearby farmland.