• Title/Summary/Keyword: Texture Region

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A Generalized Method for Extracting Characters and Video Captions (일반화된 문자 및 비디오 자막 영역 추출 방법)

  • Chun, Byung-Tae;Bae, Young-Lae;Kim, Tai-Yun
    • Journal of KIISE:Software and Applications
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    • v.27 no.6
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    • pp.632-641
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    • 2000
  • Conventional character extraction methods extract character regions using methods such as color reduction, region split and merge and texture analysis from the whole image. Because these methods use many heuristic variables and thresholding values derived from a priori knowledge, it is difficult to generalize them algorithmically. In this paper, we propose a method that can extract character regions using a topographical feature extraction method and a point-line-region extension method. The proposed method can also solve the problems of conventional methods by reducing heuristic variables and generalizing thresholding values. We see that character regions can be extracted by generalized variables and thresolding values without using a priori knowledge of character region. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is over 98%.

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Application Research on Obstruction Area Detection of Building Wall using R-CNN Technique (R-CNN 기법을 이용한 건물 벽 폐색영역 추출 적용 연구)

  • Kim, Hye Jin;Lee, Jeong Min;Bae, Kyoung Ho;Eo, Yang Dam
    • Journal of Cadastre & Land InformatiX
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    • v.48 no.2
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    • pp.213-225
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    • 2018
  • For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

Brick Path Recognition Using Image Shape Pattern and Texture Feature (영상의 형태 패턴과 텍스처 특징을 이용한 보도블록의 인식방법)

  • Woo, Byung-Seok;Yang, Sung-Min;Jo, Kang-Hyun
    • Journal of Korea Multimedia Society
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    • v.15 no.4
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    • pp.472-484
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    • 2012
  • Raised or plain block is widely used for the pedestrian's safe passage. The insincere construction, insufficient maintenance and obstacle overlaid on the pavement cause pedestrian's accidents. This paper proposes a method to detect brick path by analyzing the shape pattern and texture feature of brick located in visible distance for a safe passage. A brick appears to a regular type because of its specific shape which repeats with its sized gap and its type varies according to the surrounding environment or use. This paper shows a method which extracts the shape pattern by analyzing single surface polygon and its frequency appearing in road area. The shape pattern is used to detect similar shape regions. Some regions are not detected because extraneous substances or chopped bricks distort the original shape. This problem can be solved by analyzing the texture feature vector. The analyzed vector of the previously detected regions yields the Gaussian distribution. This value in each undetected region is computed and checked whether it's satisfied with Gaussian distribution or not. The satisfied region is detected as the brick path. The experiment was performed with the various type's bricks to recognize so that the results showed as accurate as 95.9% in average.

Depth Image Upsampling Algorithm Using Selective Weight (선택적 가중치를 이용한 깊이 영상 업샘플링 알고리즘)

  • Shin, Soo-Yeon;Kim, Dong-Myung;Suh, Jae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.7
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    • pp.1371-1378
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    • 2017
  • In this paper, we present an upsampling technique for depth map image using selective bilateral weights and a color weight using laplacian function. These techniques prevent color texture copy problem, which problem appears in existing upsamplers uses bilateral weight. First, we construct a high-resolution image using the bicubic interpolation technique. Next, we detect a color texture region using pixel value differences of depth and color image. If an interpolated pixel belongs to the color texture edge region, we calculate weighting values of spatial and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Otherwise we use color weight instead of depth weight. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

Walking assistance system using texture for visually impaired person (질감 특징을 이용한 시각장애인용 보행유도 시스템)

  • Weon, Sun-Hee;Choi, Hyun-Gil;Kim, Gye-Young
    • 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.

Effect of Shear Deformation During Drawing on Inhomogeneous Microstructures and Textures in High Purity Copper Wires After Annealing (고순도 구리 선재의 어닐링 후 불균질 미세조직과 집합조직에 미치는 신선 시 전단 변형의 영향)

  • Park, Hyun;Kim, Sang-Hyeok;Kim, Se-Jong;Lee, Hyo-Jong
    • Korean Journal of Metals and Materials
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    • v.56 no.12
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    • pp.861-869
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    • 2018
  • To determine the origin of the inhomogeneous microstructure and texture observed in drawn and annealed high purity copper wires, two kinds of drawing process conditions and their influence was investigated. The regular condition, based on a symmetric die, and a condition designed intentionally to produce an inhomogeneous shear deformation using an asymmetric die were employed. The difference in intensity of <111>-<100> distributed texture between the two wires confirmed that the wire drawn under the asymmetric die condition experienced a higher amount of shear deformation. The extensive shear strain in the wire drawn under the asymmetric die condition gave rise to inhomogeneous primary and secondary recrystallization behavior. After annealing at $200^{\circ}C$, grains with <100> texture, which were larger than the surrounding recrystallized grains, were extensively present on one half circle of the wire drawn under the asymmetric die condition, while larger grains with <100> were sparsely observed around the middle region of the wire drawn under the regular condition. Interestingly, the area where the larger grains with <100> texture existed was identical to the area where the high shear strain occurred during drawing in both wires. During annealing at $400^{\circ}C$, grains with <112> texture started to grow abnormally at the center of both wires as a result of secondary recrystallization. After annealing at $900^{\circ}C$ grains with <112> due to secondary recrystallization occupied the entire region of the wire drawn under the regular condition. On the other hand, in the wire drawn under the asymmetric die condition and then annealed at $900^{\circ}C$, the <100> oriented grains as a result of the normal grain growth of the larger <100> grains which were observed after annealing at $200^{\circ}C$, coexisted with the abnormally grown <112> grains. These results indicate that dynamic recrystallization induced by the shear strain during drawing plays an important role in the inhomogeneity of the microstructure and texture of wires after annealing.

Variable Block Size Transform Coding Using Segmented Information (영역 분할 정보를 이용한 가변 블록 크기 변환 부호화)

  • 오정수;김진태;최종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.1
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    • pp.72-80
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    • 1994
  • In this paper, a new variable block-size transform coding algorithm using information of segmentation is proposed. In general variable block-size transform coding algorithms, the information which is used to form variable blocks is thrown away, but in the proposed algorithm, the information of segmentation which is composed of texture and contour information is maintained for efficient coding. That is, the number of blocks can be reduced by contour information, a DC component of block can be predicted by texture information, and the region compensation, which reduces mean difference between regions, using texture and contour information can diminish the magnitude of AC components. The result is that the proposed algorithm has improved highly the coding efficiency of DC and AC components.

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Color Image Coding Based on Shape-Adaptive All Phase Biorthogonal Transform

  • Wang, Xiaoyan;Wang, Chengyou;Zhou, Xiao;Yang, Zhiqiang
    • Journal of Information Processing Systems
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    • v.13 no.1
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    • pp.114-127
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    • 2017
  • This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test color images reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.

Backlight Compensation by Using a Novel Region of Interest Extraction Method (새로운 관심영역 추출 방법을 이용한 역광보정)

  • Seong, Joon Mo;Lee, Seong Shin;Lee, Songwook
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.6
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    • pp.321-328
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    • 2017
  • We have implemented a technique to correct the brightness, saturation, and contrast of an image according to the degree of light, and further compensate the backlight. Backlight compensation can be done automatically or manually. For manual backlight compensation, we have to select the region of interest (ROI). ROI can be selected by connecting the outline of the desired object. We make users select the region delicately with the new magnetic lasso tool. The previous lasso tool has a disadvantage that the start point and the end point must be connected. However, the proposed lasso tool has the advantage of selecting the region of interest without connecting the start point and the end point. We can automatically obtain various results of backlight compensation by adjusting the number of k-means clusters for texture extraction and the threshold value for binarization.

Spatial Histograms for Region-Based Tracking

  • Birchfield, Stanley T.;Rangarajan, Sriram
    • ETRI Journal
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    • v.29 no.5
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    • pp.697-699
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    • 2007
  • Spatiograms are histograms augmented with spatial means and covariances to capture a richer description of the target. We present a particle filtering framework for region-based tracking using spatiograms. Unlike mean shift, the framework allows for non-differentiable similarity measures to compare two spatiograms; we present one such similarity measure, a combination of a recent weighting scheme and histogram intersection. Experimental results show improved performance with the new measure as well as the importance of global spatial information for tracking. The performance of spatiograms is compared with color histograms and several texture histogram methods.

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