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Fast localised active contour for inhomogeneous image segmentation
Duc Bui, Toan,Ahn, Chunsoo,Shin, Jitae IET 2016 IET image processing Vol.10 No.6
<P>The localised active contour framework has been widely used for image segmentation because it provides reliable results for inhomogeneous images. However, its computational complexity remains an issue. In this study, the authors introduce a fast algorithm based on the localised active contour framework. A key concept of the proposed algorithm is its consideration of the curve evolution based on the speed function only at active points that change across time, rather than at all points in a narrow band. This approach reduces computational time in the localised active contour. The authors additionally propose a modified speed function to address inhomogeneous image segmentation. The experimental results demonstrate significant advantages of the proposed method over existing methods, both in terms of computational efficiency and segmentation accuracy, for homogeneous and inhomogeneous images.</P>
A Study on Partitioning Freeform Surface and Tool Selection Method for 3-Axes CNC Machining
Bui Ngoc Tuyen,Hoang Van Quy,Duc-Toan Nguyen Korean Society for Precision Engineering 2019 한국정밀공학회지 Vol.36 No.9
Freeform surfaces are widely used in various industries. However, they require much time to be machined because of complicated geometry. To increase machining productivity, partitioning methods for freeform surface have been proposed by several previous studies regarding selection of cutting tools and tool-path. This paper proposes a new partitioning method based on Gaussian and mean curvatures to define boundaries of local patches using Freeman algorithm. Simulation results with a B-Spline surface show that the proposed method combined with cutting tool selection strategies can reduce machining time and surface roughness when compared with the non-partitioned method.
Bui Van-Bien,Banh Tien-Long,Nguyen Duc-Toan 한국정밀공학회 2019 한국정밀공학회지 Vol.36 No.8
From 2010, the first version of Microsoft Kinect, a low-cost RGB-D camera, was released which used structured light technology to capture depth information. This device has been widely applied in many segments of the industry. In July 2014, the second version of Microsoft Kinect was launched with improved hardware. Obtaining point clouds of an observed scene with high frequency being possible leads to imaging its application to meeting the demand of 3D data acquisition. However, evaluating device capacity for mechanical part modeling has been a challenge needed to be solved. This paper intends to enhance acquired depth maps of the Microsoft Kinect v2 device for mechanical part modeling and receive an assessment about the accuracy of 3D reconstruction. Influence of materials for mechanical part modeling is also evaluated. Additionally, experimental methodology for 3D modeling of the mechanical part is finally reported to ascertain the proposed model in this paper.
Neural-network-based Impulse Noise Removal Using Group-based Weighted Couple Sparse Representation
( Yongwoo Lee ),( Toan Duc Bui ),( Jitae Shin ),( Byung Tae Oh ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.
Nguyen, Van-Toan,Tran, Quoc Chinh,Quang, Nguyen Duc,Nguyen, Ngoc-Anh,Bui, Van-Tien,Dao, Van-Duong,Choi, Ho-Suk Elsevier 2018 Journal of alloys and compounds Vol.766 No.-
<P><B>Abstract</B></P> <P>The improvement of the catalytic performance for methanol and formic acid oxidation reactions remains a key issue for the development of a new generation of direct methanol and formic acid fuel cells. This study reports a simple approach, using selective chemical etching for the synthesis of unique nitrogen-doped carbon dot/Pt<SUB>84</SUB>Pd<SUB>16</SUB> (N-Cdot/Pt<SUB>84</SUB>Pd<SUB>16</SUB>) nano-network structure at room temperature with excellent electrocatalytic properties. The obtained nano-network hybrid material exhibits significant enhancement of the electrocatalytic activity for the electro-oxidation reaction of both methanol and formic acid with current densities of 999.0 and 1919.5 mA/mg<SUB>metal</SUB>, respectively, compared with the commercial ones of 751.32 and 806.02 mA/mg<SUB>metal</SUB>, respectively. Furthermore, the N-Cdot/Pt<SUB>84</SUB>Pd<SUB>16</SUB> nano-network hybrid materials exhibit excellent stability and hydrophilic dispersibility at room temperature.</P> <P><B>Highlights</B></P> <P> <UL> <LI> N-Cdot/PtPd nanonetwork hybrid material is synthesized at room temperature. </LI> <LI> A simple coreduction and a selective chemical etching are applied to the synthesis. </LI> <LI> It generates a nano-network structure with excellent electrocatalytic properties. </LI> <LI> N-Cdot functions as a uniform interconnection between the nanohybrid materials. </LI> <LI> The hybrid exhibits significant enhancement of the activity for both MOR and FAOR. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
이용우,안천수,신지태,Lee, Yong-Woo,Bui, Toan Duc,Ahn, Chunsoo,Shin, Jitae 대한의용생체공학회 2015 의공학회지 Vol.36 No.2
Osteoarthritis is the most common chronic joint disease in the world. With its progression, cartilage thickness tends to diminish, which causes severe pain to human being. One way to examine the stage of osteoarthritis is to measure the cartilage thickness. When it comes to inter-subject study, however, it is not easy task to compare cartilage thickness since every human being has different cartilage structure. In this paper, we propose a method to assess cartilage defect using MRI inter-subject thickness comparison. First, we used manual segmentation method to build accurate atlas images and each segmented image was labeled as articular surface and bone-cartilage interface in order to measure the thickness. Secondly, each point in the bone-cartilage interface was assigned the measured thickness so that the thickness does not change after registration. We used affine transformation and SyGN to get deformation fields which were then applied to thickness images to have cartilage thickness atlas. In this way, it is possible to investigate pixel-by-pixel thickness comparison. Lastly, the atlas images were made according to their osteoarthritis grade which indicates the degree of its progression. The result atlas images were compared using the analysis of variance in order to verify the validity of our method. The result shows that a significant difference is existed among them with p < 0.001.