• Journal of Environmental Science International
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• v.21 no.9
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• pp.1059-1068
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• 2012

The purpose of this study was to develope the environmentally favorable method of roller compacted soil concrete pavement using industrial waste red mud. Red mud was the major solid waste produced in the process of alumina extraction from bauxite(Bayer process). For recycling purpose, red mud was treated and applied to use as concrete admixtures. To this end, laboratory test such as compressive strength of soil concrete, and field test such as construction characteristics of soil concrete pavement, had been conducted. From the study results, the compressive strength of soil concrete was strongly related to its matrix proportion and compaction energy. The optimum mix proportion was comprised of cement 300 $kg/m^3$, water 110 $kg/m^3$, fine aggregate 600 $kg/m^3$, course aggregate 1400 $kg/m^3$, red mud admixture 50 $kg/m^3$ and compaction energy above 2.86 $cm-kgf/m^3$. The $7^{th}$-day and $28^{th}$-day mean compressive strength of soil concrete were 43.8 MPa and 53.3 MPa each under the optimum condition. Pavement application of soil concrete using red mud admixture indicated that the proposed method was simple in case of construction and showed a good surface texture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6043-6062
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• 2019

Low-rank matrix decomposition has shown its capability in many applications such as image in-painting, de-noising, background reconstruction and defect detection etc. In this paper, we consider the texture background of rail track images and the sparse foreground of the defects to construct a low-rank matrix decomposition model with block sparsity for defect inspection of rail tracks, which jointly minimizes the nuclear norm and the 2-1 norm. Similar to ADM, an alternative method is proposed in this study to solve the optimization problem. After image decomposition, the defect areas in the resulting low-rank image will form dark stripes that horizontally cross the entire image, indicating the preciselocations of the defects. Finally, a two-stage defect extraction method is proposed to locate the defect areas. The experimental results of the two datasets show that our algorithm achieved better performance compared with other methods.

• 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 Korea Game Society
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• v.11 no.2
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• pp.115-129
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• 2011

In this paper, we will introduce some method about retrieving suitable images to game or adjusting game difficulty in enjoying some contents like mini-game. It will use the technology about extracting color and texture features in content-based image retrieval in image processing. So in card game, it select card image automatically. And by controlling seed image number, we can adjusting game difficulty. Through the experiment, it shows that our image retrieval method can retrieve more useful images that can be used in game than others.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3333-3340
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• 2000

Recently, Requnremeni for video data have been increased rapidly by high progress of both hardware and cornpression technique. Because digital video data are unformed and mass capacity, it needs various retrieval techniquesjust as contednt-based rehieval Superimposed-caption ina digital video can help us to analyze the video story easier and be used as indexing information for many retrieval techniques In this research we propose a new method that segments the caption as analyzing texture eature of caption regions in each video frame, and that extracts the accurate scope of superimposed-caption frame and its key regions and color by measunng cominuity of caption regions between frames

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.90-95
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• 2012

Remotely sensed data provide valuable information on land monitoring due to multi-temporal observation over large areas. Especially, high resolution imagery with 0.6~1.0 m spatial resolutions contain a wealth of information and therefore are very useful for thematic mapping and monitoring change in urban areas. Recently, remote sensing technology has been successfully utilized for natural disaster monitoring such as forest fire, earthquake, and floods. In this paper, an efficient change detection method based on texture differences observed from high resolution multi-temporal data sets is proposed for mapping disaster damage and extracting damage information. It is composed of two parts: feature extraction and detection process. Timely and accurate information on disaster damage can provide an effective decision making and response related to damage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.585-589
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• 2002

In this paper, hierarchical retrieval system based on efficient feature extraction is proposed. In order to retrieval the image with robustness for geometrical transformation such as translation, scaling, and rotation. After performing the 2-level wavelet transform on image, We extract moment in low-level subband which was subdivided into subimages and texture feature, contrast of GLCM(Gray Level Co-occurrence Matrix). At first we retrieve the candidate images in database by the ones of image. To perform a more accurate image retrieval, the edge information on the high-level subband was subdivided horizontally, vertically and diagonally. And then, the energy rate of edge per direction was determined and used to compare the energy rate of edge between images for higher accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.203-208
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• 2006

The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. This paper has complemented the problem caused by the absence of space information that is a weak point of the existing color histogram method by assigning regions of features, and raised accuracy by adding texture and shape information. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we has solved these problems by assignment of weight applying fuzzy integral. As a result of experimenting with 1,000 color images, the proposed method showed better precision and recall than the existing method.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.133-139
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• 2006

Multimedia data is increasing rapidly by development of computer Information technology. Specially, quick and accurate processing of image data is required in image retrieval field. But it is difficult to guarantee both quickness and accuracy. This article suggests the algorithm that extracts representative features of image using genetic algorithm to solve this problem. This algorithm guarantees quickness and accuracy of retrieval by extracting representative features of image. We used color and texture as feature of image. Experiment shows that feature extracting method that is proposed is more accurate than existing study. So this study establishes propriety of method that is proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6000-6017
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• 2018

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.