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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Civil Engineering Infrastructures Journal
- نوع مقاله: Journal Article
- کلمات کلیدی: Algorithm,Crack Length,Crack Width,Cracks,Digital Image Processing
- چکیده:
- چکیده انگلیسی: The elements of the concrete structure are most frequently affected by cracking. Crack detection is essential to ensure safety and performance during its service life. Cracks do not have a regular shape, in order to achieve the exact dimensions of the crack; the general mathematical formulae are by no means applicable. The authors have proposed a new method which aims to measure the crack dimensions of the concrete by utilizing digital image processing technique. A new algorithm has been defined in MATLAB. The acquired data has been analyzed to obtain the most precise results. Here both the length and width of the crack are obtained from image processing by removing background noise for the accuracy of measurement. A semi-automatic methodology is adapted to measure the crack length and crack width. The applicability of the program is verified with the past literature works.
- انتشار مقاله: 01-09-1396
- نویسندگان: T. Barkavi,Natarajan Chidambarathanu
- مشاهده
- جایگاه : پژوهشی
- مجله: Civil Engineering Infrastructures Journal
- نوع مقاله: Journal Article
- کلمات کلیدی: Algorithm,Crack Length,Crack Width,Cracks,Digital Image Processing
- چکیده:
- چکیده انگلیسی: The elements of the concrete structure are most frequently affected by cracking. Crack detection is essential to ensure safety and performance during its service life. Cracks do not have a regular shape, in order to achieve the exact dimensions of the crack; the general mathematical formulae are by no means applicable. The authors have proposed a new method which aims to measure the crack dimensions of the concrete by utilizing digital image processing technique. A new algorithm has been defined in MATLAB. The acquired data has been analyzed to obtain the most precise results. Here both the length and width of the crack are obtained from image processing by removing background noise for the accuracy of measurement. A semi-automatic methodology is adapted to measure the crack length and crack width. The applicability of the program is verified with the past literature works.
- انتشار مقاله: 01-09-1396
- نویسندگان: T. Barkavi,Natarajan Chidambarathanu
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Colonoscopy,Colon cancer,Local Binary Pattern (LBP),Color,Discrete Cosine Transform (DCT)
- چکیده:
- چکیده انگلیسی:
Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods.- انتشار مقاله: 06-06-1395
- نویسندگان: Geetha K,Rajan C
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Support vector machine,Receiver Operating Curve (ROC),Surface Acoustic Wave (SAW),Human Epidermal Growth Receptor (HER-2)
- چکیده:
- چکیده انگلیسی:
Breast Cancer one of the appalling diseases among the middle-aged women and it is a foremost threatening death possibility cancer in women throughout the world. Earlier prognosis and preclusion reduces the conceivability of death. The proposed system beseech various data mining techniques together with a real-time input data from a biosensor device to determine the disease development proportion. Surface acoustic waves (SAW) biosensor empowers a label-free, worthwhile and straight detection of HER-2/neu cancer biomarker. The output from the biosensor is fed into the proposed system as an input along with data collected from Winconsin dataset. The complete dataset are processed using data mining classification algorithms to predict the accuracy. The exactness of the proposed model is improved by ranking attributes by Ranker algorithm. The results of the proposed model are highly gifted with an accuracy of 79.25% with SVM classifier and an ROC area of 0.754 which is better than other existing systems. The results are used in designing the proper drug thereby improving the survivability of the patients.- انتشار مقاله: 13-04-1396
- نویسندگان: Sountharrajan S,Karthiga M,Suganya E,Rajan C
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Support vector machine,Receiver Operating Curve (ROC),Surface Acoustic Wave (SAW),Human Epidermal Growth Receptor (HER-2)
- چکیده:
- چکیده انگلیسی:
Breast Cancer one of the appalling diseases among the middle-aged women and it is a foremost threatening death possibility cancer in women throughout the world. Earlier prognosis and preclusion reduces the conceivability of death. The proposed system beseech various data mining techniques together with a real-time input data from a biosensor device to determine the disease development proportion. Surface acoustic waves (SAW) biosensor empowers a label-free, worthwhile and straight detection of HER-2/neu cancer biomarker. The output from the biosensor is fed into the proposed system as an input along with data collected from Winconsin dataset. The complete dataset are processed using data mining classification algorithms to predict the accuracy. The exactness of the proposed model is improved by ranking attributes by Ranker algorithm. The results of the proposed model are highly gifted with an accuracy of 79.25% with SVM classifier and an ROC area of 0.754 which is better than other existing systems. The results are used in designing the proper drug thereby improving the survivability of the patients.- انتشار مقاله: 13-04-1396
- نویسندگان: Sountharrajan S,Karthiga M,Suganya E,Rajan C
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Support vector machine,Receiver Operating Curve (ROC),Surface Acoustic Wave (SAW),Human Epidermal Growth Receptor (HER-2)
- چکیده:
- چکیده انگلیسی:
Breast Cancer one of the appalling diseases among the middle-aged women and it is a foremost threatening death possibility cancer in women throughout the world. Earlier prognosis and preclusion reduces the conceivability of death. The proposed system beseech various data mining techniques together with a real-time input data from a biosensor device to determine the disease development proportion. Surface acoustic waves (SAW) biosensor empowers a label-free, worthwhile and straight detection of HER-2/neu cancer biomarker. The output from the biosensor is fed into the proposed system as an input along with data collected from Winconsin dataset. The complete dataset are processed using data mining classification algorithms to predict the accuracy. The exactness of the proposed model is improved by ranking attributes by Ranker algorithm. The results of the proposed model are highly gifted with an accuracy of 79.25% with SVM classifier and an ROC area of 0.754 which is better than other existing systems. The results are used in designing the proper drug thereby improving the survivability of the patients.- انتشار مقاله: 13-04-1396
- نویسندگان: Sountharrajan S,Karthiga M,Suganya E,Rajan C
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Colon cancer,Video Capsule Endoscopy,Colonoscopy, Segmentation,Genetic Fuzzy classifier
- چکیده:
- چکیده انگلیسی:
Methods: Colonoscopy is a technique for examine colon cancer, polyps. In endoscopy, video capsule is universally used mechanism for finding gastrointestinal stages. But both the mechanisms are used to find the colon cancer or colorectal polyp. The Automatic Polyp Detection sub-challenge conducted as part of the Endoscopic Vision Challenge (http://endovis.grand-challenge.org). Method: Colonoscopy may be primary way of improve the ability of colon cancer detection especially flat lesions. Which otherwise may be difficult to detect. Recently, automatic polyp detection algorithms have been proposed with various degrees of success. Though polyp detection in colonoscopy and other traditional endoscopy procedure based images is becoming a mature field, due to its unique imaging characteristics, detecting polyps automatically in colonoscopy is a hard problem. So the proposed video capsule cam supports to diagnose the polyps accurate and easy to identify its pattern. Existing methodology mainly concentrated on high accuracy and less time consumption and it uses many different types of data mining techniques. To analyse these high resolution video scale image we have to take segmentation of image in pixel level binary pattern with the help of a mid-pass filter and relative gray level of neighbours. This work consists of three major steps to improve the accuracy of video capsule endoscopy such as missing data imputation, high dimensionality reduction or feature selection and classification. The above steps are performed using a dataset called endoscopy polyp disease dataset with 500 patients. Our binary classification algorithm relieves human analyses using the video frames. SVM has given major contribution to process the dataset. Results: In this paper the key aspect of proposed results provide segmentation, binary pattern approach with Genetic Fuzzy based Improved Kernel Support Vector machine (GF-IKSVM) classifier. The segmented images all are mostly round shape. The result is refined via smooth filtering, computer vision methods and thresholding steps. Conclusion: Our experimental result produces 94.4% accuracy in that the proposed fuzzy system and genetic Fuzzy, which is higher than the methods, used in the literature. The GF-IKSVM classifier is well-organized and provides good accuracy results for patched VCE polyp disease diagnosis.- انتشار مقاله: 09-01-1396
- نویسندگان: Geetha K,Rajan C
- مشاهده