• Computers and Concrete
• /
• v.7 no.6
• /
• pp.511-522
• /
• 2010

A color based segmentation procedure and a modified signature technique have been applied to the detection and analyses of complicated void shapes in cemented materials. The gray-scale segmentation and available signature methods were found to be inefficient especially for the analyses of complicated void shapes. The applicability of the developed methodology has been demonstrated on artificially prepared cemented materials made of self compacted concrete material. In order to characterize the void shapes in the investigated sample images, two new shape parameters called as coefficients of inclusion and exclusion have been proposed. When compared with the traditional use of the signature method, it was found that the methodology followed herein would better characterize complicated void shapes. The methodology followed in this study may be applied to the analysis of complicated void shapes that are often encountered in other cementitious materials such as clays and rocks.

• Journal of the Semiconductor & Display Technology
• /
• v.9 no.3
• /
• pp.59-63
• /
• 2010

This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Journal of the Semiconductor & Display Technology
• /
• v.8 no.2
• /
• pp.23-29
• /
• 2009

To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

• Investigative Magnetic Resonance Imaging
• /
• v.25 no.3
• /
• pp.189-192
• /
• 2021

Anti-myelin oligodendrocyte glycoprotein (anti-MOG) syndrome is an immune-mediated inflammatory condition of the central nervous system, which usually involves spinal cord and optic nerves. Herein, we studied the case of a 57-year-old female patient who presented with acute/subacute symptoms of sphincter dysfunction, paraparesis, and ocular pain. The patient was diagnosed with anti-MOG syndrome with findings resembling snake-eye appearance (SEA), characterized by nearly symmetrical round high signal intensity lesions located at anterior horns (gray matter) on T2-weighted image.

• Journal of the Korean Society of Visualization
• /
• v.19 no.1
• /
• pp.68-73
• /
• 2021

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.05a
• /
• pp.785-788
• /
• 2004

폐 기관지는 외부의 공기를 폐까지 전달해주는 역할을 하고 있다. 이는 병리학적, 해부학적으로 중요한 역할을 하고 있으며, 의사들에게는 기관지의 상태를 시각적으로 쉽게 판독을 할 수 있다면 폐에서 발생하는 기관지염(bronchitis), 기관지 확장증(bronchiectasis), 폐기종(pulmonary emphysema), 결핵(tuberculosis), 기흉(pneumothorax)등 여러 가지 병명을 쉽게 판독이 가능하다. 지금까지 폐 기관지에 대한 연구가 지속적으로 진행 되었으며, 2D CT 영상에서의 주변의 밀도차가 유사한 폐실 질에서의 폐기관지를 추출해 내는 것은 어려움을 Gray-scale Reconstruction과 임계치를 이용하여 추출하였다. 이는 3D 구성을 위한 전 단계로 인체 내부의 장기를 가상의 영상을 실제와 가까운 영상으로 구현하는데 쓰인다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1464-1480
• /
• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.298-301
• /
• 2011

Edge detection is an base research task in the field of image processing. Edge detection can be regarded as a technique for locating pixels of abrupt gray-level change. So with Gradient method, it can be computed easily. But it can't satisfy human naked eye. so in this paper, new algorithm based on the NLM(Non Local Means) is proposed for good performance for human naked eye.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.259-268
• /
• 2008

In an effort to increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, we present an effective 2D barcode detection algorithm from gray-level images, especially for the handheld 2D barcode recognition system. To locate the symbol inside the image, a criteria based on the block contrast is adopted, and a gray-scale projection with sub-pixel operation is utilized to segment the symbol precisely from the region of interest(ROI). Finally, the segmented ROI is normalized using the inverse perspective transformation for the following decoding processes. We also introduce the post-processing steps for decoding the QR-code. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments shows that our method is very robust and efficient in detecting the code area for the various types of 2D barcodes in real time.

• Journal of Korea Multimedia Society
• /
• v.13 no.4
• /
• pp.535-546
• /
• 2010

Digital images have undesired color casts due to various illumination conditions and intrinsic characteristics of cameras. Since the color casts in the images deteriorate performance of color representations, color correction is required for further analysis of images. In this paper, an algorithm for detection and removal of color casts is presented. The proposed algorithm consists of four steps: retrieving similar image using color by correlation, extraction of near neutral color regions, kernel density estimation, and removal of color casts. Ambiguities in near neutral color regions are excluded based on kernel density estimation by the color by correlation algorithm. The method determines whether there are color casts by chromaticity distributions in near neutral color regions, and removes color casts for color constancy. Experimental results suggest that the proposed method outperforms the gray world algorithm and the color by correlation algorithm.