• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1357-1367
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• 2013

Recently, as one of images based methods in facial expression recognition, the research which used ULBP block histogram feature and SVM classifier was performed. Due to the properties of LBP introduced by Ojala, such as highly distinction capability, durability to the illumination changes and simple operation, LBP is widely used in the field of image recognition. In this paper, we combined $LBP_{8,2}$ and $LBP_{8,1}$ to describe micro features in addition to shift, size change in calculating ULBP block histogram. From sub-windows of 660 of $LBP_{8,1}$ and 550 of $LBP_{8,2}$, ULBP histogram feature of 1210 were extracted and weak classifiers of 50 were generated using AdaBoost. By using the combined $LBP_{8,1}$ and $LBP_{8,2}$ hybrid type of ULBP histogram feature and SVM classifier, facial expression recognition rate could be improved and it was confirmed through various experiments. Facial expression recognition rate of 96.3% by hybrid boosted ULBP block histogram showed the superiority of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.77-85
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• 2011

In this paper, we propose an region segmentation and texture based feature extraction method which split the pavement and roadway from the camera which equipped to the visually impaired person during a walk. We perform the hough transformation method for detect the boundary between pavement and roadway, and devide the segmented region into 3-level according to perspective. Next step, split into pavement and roadway according to the extracted texture feature of segmented regions. Our walking assistance system use rotation-invariant LBP and GLCM texture features for compare the characteristic of pavement block with various pattern and uniformity roadway. Our proposed method show that can segment two regions with illumination invariant in day and night image, and split there regions rotation and occlution invariant in complexed outdoor image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.181-184
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• 2009

본 논문은 번호판 내 명암도 대비를 이용한 자동차 번호판 검출 기법을 제안한다. 평균값 필터와 라플라시안 필터를 사용하여 영상의 잡음을 제거하는 동시에 에지 성분을 향상시킨 후 조명 환경 변화에 강인한 번호판 내 명암도 대비 특징을 이용하여 문자 후보를 검출한다. 다음으로 검출된 문자 후보가 열을 이루는 텍스트 후보를 검출하고, 이 영역을 Otsu 이진화 기업을 사용하여 x축에 투영하였을 시 나타나는 패턴을 평가함으로써 최종적으로 자동차 번호판을 검출하게 된다. 제안하는 기법의 성능을 평가하기 위해 다수의 데이터를 사용하여 실험하였고, 이를 분석하여 제안하는 기법의 우수성을 검증하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.11-17
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• 2010

In this parer, face recognition method which can be applied to ITCS (interactive TV control system) is proposed. We extracted ULBP(uniform local binary pattern) histogram feature from infra-red images, and we detected left-right eyes and face region by using SVM classifier. Then, We implemented face recognition system which is using Gabor transform and ULBP histogram feature and applied to personal verification for ITCS.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.35-44
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• 2007

This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.54-66
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• 1997

Efficient retrieval of image data is an important research issue in multimedia database. This paper proposes a new approach to a content-based image retrieval which allows queries to be composed of the local texture patterns and the slope components of contour points. The texture patterns extracted from the source image using the graylevel co-occurrence matrix and the slope components of contour points extracted from the binary image are converted into a internal feature representation of reduced dimensionality which preserves the perceptual similarity and those features can be used in creating efficient indexing structures for a content-based image retrieval. Experimental results of the image retrievalare presented to illustrate the usefulness of this approach that demonstrates the precision 82%, the recall 87% and the average rang 3.3 in content-based image data retrieval.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.483-488
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• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.10
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• pp.67-71
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• 2011

Existing face detection systems, which are used for digital door locks, digital cameras, video surveillance systems, and so on, are software-based implementation for relatively low level resolution images. Therefore, in this case, there are difficulties in detecting faces in a real-time fashion due to the increasing amount of operational processing as well as in allowing the requirements of face detections for HD(High Definition) resolutions. A hardware approach is necessary to efficiently find faces for HD images in real-time embedded systems. This paper proposes and implements a hardware architecture for an LBP(Local Binary Pattern) operation which is a time-consuming part as one of preprocessing steps for face detection. The hardware architecture proposed in this research has been implemented and tested with a FPGA(Field Programmable Gate Array) chip, and shown that the approach guarantees efficient face detection for HD images.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.1
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• pp.35-46
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• 1998

Structural damage is used to be modeled through reductions in the stiffness of structural elements for the purpose of damage estimation of structural system. In this study, the concept of joint damage is employed for more realistic damage assessment of a steel structure. The joint damage is estimated damage based on the mode shape informations using neural networks, The beam-to-column connection in a steel frame structure is represented by a rotational spring at the fixed end of a beam element. The severity of joint damage is defined as the reduction ratio of the connection stiffness with respect to the value of the intact joint. The concept of the substructural identification is used for the localized damage assessment in a large structure. The feasibility of the proposed method is examined using an example with simulated data. It has been found that the joint damages can be reasonably estimated for the case with the measurements of the mode vectors subjected to noise.