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RISS 인기검색어
- 검색키워드
- 저자 : Shahid Ikramullah Butt (검색결과 2 건)
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Blind Signal Separation Method Based Machining Error Decomposition
Fa-Ping Zhang,Di Wu,Yan Yan,Shahid Ikramullah Butt 한국정밀공학회 2018 International Journal of Precision Engineering and Vol.19 No.2
In view of the current error separation method cannot successfully separate the dissimilar systematic error components from the whole surface machining data, a method for machining errors decomposition based on blind signal separation is proposed which can distinguish those dissimilar systematic error components. Firstly, the error transfer model to describe the errors synthesizing from the single error component caused by corresponding individual error source to the synthesis machining surface error is conducted. To determine the number of the systematic error components, the principal component analysis (PCA) method is used. Then according to the theory of blind source separation, negative entropy based fixed point algorithm is proposed to fulfill the machining error components separation, which can realize the separation of the systematic error components even in close frequency scale. Finally, a shaft surface finish turning data and a flat surface milling data are used as examples to verify the proposed method. The result shows that the proposed error separation method can effectively realize the machining error separation in close frequency scale.
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Adaptive Thresholding Technique for Segmentation and Juxtapleural Nodules Inclusion in Lung Segments
Muhammad Zia ur Rehman,Syed Omer Gilani,Syed Irtiza Ali Shah,Mohsin Jamil,Irfanullah,Shahid Ikramullah Butt 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.5
Early diagnosis of lung cancer plays crucial role in the improvement of patients' chances of survival. Computer aided detection (CAD) system has been a groundbreaking step in the timely diagnosis and identification of potential nodules (lesions). CAD system starts detection process by extracting lung regions from CT scan images, this step narrows down the region for detection. Hence saving the time consumption and reducing false positives outside the lung regions that results in the improvement of specificity of system. Proper lung segmentation significantly increases the performance of CAD systems. Different algorithms are presented by various researchers to improve segmentation results. An intensity based approach is presented in this paper for the segmentation of parenchyma and the goal is to achieve reasonable segmentation results in less time. Algorithm used in this paper is based on the Intensity based thresholding which is the fastest method for image segmentation. Images used in this research to analyze algorithm's result are taken from Lung Image Database Consortium (LIDC). Twenty random cases were picked, each having different number of slices (128 to 300). Algorithm is implemented using MatlabR2014 and a system with processor of 2.6 GHz and RAM of 4 GB. Total time taken for a single case of 128 images was 6.3 seconds and hence with an average of 49 milli sec/slice.
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