An Improved Texture Feature Extraction Method for Recognizing Emphysema in CT Images

Shao-Hu Peng,Hyun-Do Nam 한국조명·전기설비학회 2010 조명·전기설비학회논문지 Vol.24 No.11

In this study we propose a new texture feature extraction method based on an estimation of the brightness and structural uniformity of CT images representing the important characteristics for emphysema recognition. The Center-Symmetric Local Binary Pattern (CS-LBP) is first used to combine gray level in order to describe the brightness uniformity characteristics of the CT image. Then the gradient orientation difference is proposed to generate another CS-LBP code combining with gray level to represent the structural uniformity characteristics of the CT image. The usage of the gray level, CS-LBP and gradient orientation differences enables the proposed method to extract rich and distinctive information from the CT images in multiple directions. Experimental results showed that the performance of the proposed method is more stable with respect to sensitivity and specificity when compared with the SGLDM, GLRLM and GLDM The proposed method outperformed these three conventional methods (SGLDM, GLRLM, and GLDM) 7.85[%], 22.87[%], and 16.67[%] respectively, according to the diagnosis of average accuracy, demonstrated by the Receiver Operating Characteristic (ROC) curves.

Quantitative Image Analysis of Chest CT Using Gray Level Local Binary Pattern Texture Feature

Shao-Hu Peng,Khairul Muzzammil,Deok-Hwan Kim 한국콘텐츠학회 2009 ICCC International Digital Design Invitation Exhib Vol.2009 No.12

Texture feature is one of the most popular image analysis methods for computer-aided diagnosis (CAD) system. This paper presents a texture feature extraction method based on gray level local binary pattern (GLLBP) to help the diagnosis of emphysema disease using chest CT images. The proposed method allows us to extract texture features with multiple directions. Experimental results show that GLLBP can achieve better performance than the existing texture features.

블럽 검출기를 이용한 X-Ray 영상에서의 BGA 검출기법

Shao-Hu Peng,이혜정,남현도,심재선 대한전기학회 2011 정보 및 제어 심포지엄 논문집 Vol.2011 No.4

Traditional Chinese Medicine as a Remedy for Male Infertility: A Review

Shao Hu Zhou,Yu Fei Deng,Zhi Wei Weng,Hao Wei Weng,Zhi Dan Liu 대한남성과학회 2019 The World Journal of Men's Health Vol.37 No.2

Male infertility (MI) is a complex multifactorial disease, and idiopathic infertility accounts for 30% of cases of MI. At present, the evidence for the effectiveness of empirical drugs is limited, and in vitro fertilization is costly and may increase the risk of birth defects and childhood cancers. Therefore, affected individuals may feel obliged to pursue natural remedies. Traditional Chinese medicine (TCM) may represent a useful option for infertile men. It has been demonstrated that TCM can regulate the hypothalamic-pituitary-testicular axis and boost the function of Sertoli cells and Leydig cells. TCM can also alleviate inflam-mation, prevent oxidative stress, reduce the DNA fragmentation index, and modulate the proliferation and apoptosis of germ cells. Furthermore, TCM can supply trace elements and vitamins, ameliorate the microcirculation of the testis, decrease the levels of serum anti-sperm antibody, and modify epigenetic markers. However, the evidence in favor of TCM is not compel-ling, which has hindered the development of TCM. This review attempts to elucidate the underlying therapeutic mechanisms of TCM. We also explore the advantages of TCM, differences between TCM and Western medicine, and problems in existing studies. Subsequently, we propose solutions to these problems and present perspectives for the future development of TCM.

Correlation Tracking with Correcting and Adaptive Update Strategy

Shao-Hu Peng,남현도 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.5

Object tracking plays an important role in the research field of computer vision. Correlation filter (CF) based tracking algorithms have shown remarkable performance recently. However, there are two problems: (1) the online model is prone to drift due to the fixed coefficient update strategy; (2) a tracking error is susceptible to lead the failure of the following tracking task due to the absence of a correcting strategy. To deal with these limitations, we proposed a new correlation tracking filter that includes an adaptive update strategy and a correcting strategy. The adaptive update strategy is based on the confident degree of the tracking result, which can minimize the effect of image noise. And the correcting strategy is based on a four-level classifier that can enhance the error correcting ability. Based on these two strategies, the proposed CCAS not only can improve the accuracy of the correlation tracking, but also can build a detector with strong error correcting ability to handle a variety of challenges. Experiments show the proposed method has the effective correcting ability and can resist model drift. It is noted that the proposed algorithm not only outperforms other state-of-art algorithms but also runs enough fast for real time application.

A Robust Crack Filter Based on Local Gray Level Variation and Multiscale Analysis for Automatic Crack Detection in X-ray Images

Shao-Hu Peng,Hyun-Do Nam 대한전기학회 2016 Journal of Electrical Engineering & Technology Vol.11 No.4

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since Xrays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

A visual shape descriptor using sectors and shape context of contour lines

Peng, Shao-Hu,Kim, Deok-Hwan,Lee, Seok-Lyong,Chung, Chin-Wan Elsevier 2010 Information sciences Vol.180 No.16

<P><B>Abstract</B></P><P>This paper describes a visual shape descriptor based on the sectors and shape context of contour lines to represent the image local features used for image matching. The proposed descriptor consists of two-component feature vectors. First, the local region is separated into sectors and their gradient magnitude and orientation values are extracted; a feature vector is then constructed from these values. Second, local shape features are obtained using the shape context of contour lines. Another feature vector is then constructed from these contour lines. The proposed approach calculates the local shape feature without needing to consider the edges. This can overcome the difficulty associated with textured images and images with ill-defined edges. The combination of two-component feature vectors makes the proposed descriptor more robust to image scale changes, illumination variations and noise. The proposed visual shape descriptor outperformed other descriptors in terms of the matching accuracy: 14.525% better than SIFT, 21% better than PCA-SIFT, 11.86% better than GLOH, and 25.66% better than the shape context.</P>

A Robust Crack Filter Based on Local Gray Level Variation and Multiscale Analysis for Automatic Crack Detection in X-ray Images

Peng, Shao-Hu,Nam, Hyun-Do The Korean Institute of Electrical Engineers 2016 Journal of Electrical Engineering & Technology Vol.11 No.4

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

An Improved Texture Feature Extraction Method for Recognizing Emphysema in CT Images

Peng, Shao-Hu,Nam, Hyun-Do The Korean Institute of IIIuminating and Electrica 2010 조명·전기설비학회논문지 Vol.24 No.11

In this study we propose a new texture feature extraction method based on an estimation of the brightness and structural uniformity of CT images representing the important characteristics for emphysema recognition. The Center-Symmetric Local Binary Pattern (CS-LBP) is first used to combine gray level in order to describe the brightness uniformity characteristics of the CT image. Then the gradient orientation difference is proposed to generate another CS-LBP code combining with gray level to represent the structural uniformity characteristics of the CT image. The usage of the gray level, CS-LBP and gradient orientation differences enables the proposed method to extract rich and distinctive information from the CT images in multiple directions. Experimental results showed that the performance of the proposed method is more stable with respect to sensitivity and specificity when compared with the SGLDM, GLRLM and GLDM. The proposed method outperformed these three conventional methods (SGLDM, GLRLM, and GLDM) 7.85[%], 22.87[%], and 16.67[%] respectively, according to the diagnosis of average accuracy, demonstrated by the Receiver Operating Characteristic (ROC) curves.

지역명암대비 및 블롭형태 유사도에 기반한 유연한 블롭 검출기

팽소호(Shao Hu peng),남현도(Hyun Do Nam),심재선(Jae-Sun Shim) 대한전기학회 2012 정보 및 제어 심포지엄 논문집 Vol.2012 No.10