• Journal of Korea Multimedia Society
• /
• v.8 no.4
• /
• pp.492-501
• /
• 2005

In this paper, we proposed the new segmentation method of optic nerve head and optic cub to consider the depth of optic nerve head on stereo fundus image. We analyzed the error factor of stereo matching on stereo fundus image, and compensated them. For robust extraction of optic nerve head and optic cub, we proposed the modified active contour model to consider the 3D depth of optic nerve head. As experiment result to various stereo fundus images, we confirmed that proposed method can segment optic nerve head and optic cup effectively.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.2
• /
• pp.670-675
• /
• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.3
• /
• pp.943-952
• /
• 2000

The surface reconstruction problem from a set of wire-frame contours is very important in diverse fields such as medical imaging or computer animation. In this paper, surface triangulation method is proposed for solving the problem. Generally, many optimal triangulation techniques suffer from the large computation time but heuristic approaches may produce very unnatural surface when contours are widely different in shape. To compensate the disadvantages of these approaches, we propose a new heuristic triangulation method which iteratively decomposes the surface generation problem from a band (a pair of vertices chain) into tow subproblems from two sub-bands. Generally, conventional greedy heuristic contour triangulation algorithm, suffer from the drastic error propagation during surface modeling when the adjacent contours are different in shape. Our divide-and-conquer algorithm, called band partitioning algorithm, processes eccentric parts of the contours first with more global information. Consequently, the resulting facet model becomes more stable and natural even though the shapes are widely different. An interesting property of our method is hat it supports multi-resolution capability in surface modeling time. According to experiments, it is proved to be very robust and efficient in many applications.

• Journal of Biomedical Engineering Research
• /
• v.24 no.4
• /
• pp.247-257
• /
• 2003

This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

• International Journal of Precision Engineering and Manufacturing
• /
• v.8 no.3
• /
• pp.64-70
• /
• 2007

Of all the rapid tooling (RT) methods currently available, thick-layer laminated tooling is the most suitable for large-scale, low-cost dies and molds. Currently, the determination of a lamina's contour or profile and the associated slicing algorithms are based on existing rapid prototyping (RP) data manipulation technology. This paper presents a new adaptive slicing algorithm developed exclusively for profiled edge laminae (PEL) tooling PEL tooling is a thick-layer RT technique that involves the assembly of an array of laminae, whose top edges are simultaneously profiled and beveled using a line-of-sight cutting method based on a CAD model of the intended tool surface. The cutting profiles are based on the intersection curve obtained directly from the CAD model to ensure geometrical accuracy. The slicing algorithm determines the lamina thicknesses that minimize the dimensional error using a new tool shape error index. At the same time, the algorithm considers the available lamination thicknesses and desired lamina interface locations. We demonstrate the new slicing algorithm by developing a simple industrial PEL tool based on a CAD part shape.

• Journal of Broadcast Engineering
• /
• v.13 no.5
• /
• pp.651-661
• /
• 2008

This paper proposes a novel contrast enhancement (CE) algorithm for color images using the modified error diffusion (ED). After conventional color histogram equalization (HE), artifacts such as false contours are produced in the contrast enhanced image. The proposed CE algorithm using the modified ED consists of two parts: CE and ED. In the first part, a low-contrast input image is enhanced by the conventional HE method. In the second part, we use the modified ED algorithm. The inputs of the second part are the average and scaled difference images of the original color input image and the HE image, in which the scaled color difference image is diffused by the ED algorithm. In the proposed algorithm, the modified ED algorithm reduces the artifacts produced in the HE image, and increases the number of color levels. Computer simulations with a number of low-contrast color images show the effectiveness of the proposed CE method in terms of the visual quality as well as the probability mass function. It can be used as a post-processing for CE with simultaneous artifact reduction in various display devices.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.4
• /
• pp.27-36
• /
• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.

• Journal of Sasang Constitutional Medicine
• /
• v.19 no.2
• /
• pp.22-29
• /
• 2007

1. Objectives Sasang Contitutional Medicine, a part of the traditional Korean medical lore, treats illness through a constitutional typing system that categorizespeople into four constitutional types. A few of the important criteria for differentiating the constitutional types are external appearances, inner state of mind, and pathological patterns. We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the mechanical accuracy of the 3D-AFRA hardware. 2. Methods Several objects of different shapes (cube, cylinder, cone, pyramid) were each scanned 10 times using the 3D Automatic Face Recognition Apparatus (3D-AFRA). The results were then compared and analyzed with data retrieved through a laser scanner known for its high accuracy. The error rates were analyzed for each grid point of facial contour scanned with Rapidform2006 (Rapidform2006 is a 3D scanning software that collects grid point data for contours of various products and products and product parts through 3D scanners and other 3D measuring devices; the grid point data thusly acquired is then used to reconstruct highly precise polygon and curvature models). 3. Results and Conclusions The average error rate was 0.22mm for the cube, 0.22mm for the cylinder, 0.125mm for the cone, and 0.172mm for the pyramid. The visual data comparing error rates for measurement figures retrieved with Rapidform2006 is shown in $Fig.3{\sim}Fig.6$. Blue tendency indicates smaller error rates, while red indicates greater error rates The protruding corners of the cube display red, indicating greater error rates. The cylinder shows greater error rates on the edges. The pyramid displays greater error rates on the base surface and around the vertex. The cone also shows greater error around the protruding edge.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.4
• /
• pp.384-390
• /
• 2012

In this paper, we analyzed the navigation error of TERCOM (TErrain COntour Matching), which is TRN (Terrain Referenced Navigation) batch processing, caused by scale factor error of radar altimeter and proved the possibility of false position fix when we use the TERCOM's feature matching algorithm. Based on these, we proposed the new TRN batch processing algorithm using the slope measurements of terrain. The proposed technique measures on periodic changes in the slope of the terrain elevation profile, and these measurements are used in the feature matching algorithm. By using the slope of terrain data, the impact of scale factor errors can be compensated. By simulation, we verified improved outcome using this approach compared to the result using the conventional method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.5
• /
• pp.497-502
• /
• 1997

In this study an automatic rolling-coil labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel mill. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moments invariant algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transferred by asynchronous communication method. Therefore, even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.