• Journal of information and communication convergence engineering
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• v.15 no.4
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• pp.250-255
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• 2017

In this paper, we propose a method of detecting the region for measuring intima-media thickness (IMT). The existing methods for IMT measurement are automatic, but the region used for measuring IMT is not detected automatically but often set by the user. Therefore, research on detecting the intima-media region is needed for fully automated IMT measurement. The proposed method uses a morphological feature of the carotid artery visible as two long high-brightness horizontal lines at the upper and lower parts. It uses Gaussian blurring, ends-in search stretching, color quantization using a color-importance-based self-organizing map, and morphological operations to emphasize and to detect the morphological feature. The experimental results for evaluating the performance of the proposed method showed a 97.25% (106/109) success rate. Therefore, the proposed method can be used to develop a fully automated IMT measurement system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.823-830
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• 2010

This study was designed to examine the morphological measurement and characteristics of trabecullae based on femoral radiographic image for prediction of osteoporosis. Study subjects were 34 females (average age of 62.1 years) and 6 males (average age of 60.1 years), they were categorized into normal group and osteoporosis group in accordance with the T-score value. Measurement of the bone density of femoral bone was measured with DEXA(Dual Energy X-ray absorptiometry). ROI(Region of interests) was selected on femoral neck and trochanter. Characteristics of trabecullae was analyzed by using the skeletonization analysis of trabecular image. Morphological measurement was analyzed through femoral radiographic image in order to examine the correlation with osteoporosis. The result demonstrated statistically significant correlation between neck cortical thickness, shaft width, shaft cortical thickness, periphery, mean gray level and trabeculae area with BMD average (T-score) of femoral part. The results show that morphological measurement and characteristics of trabecullae based on femoral radiographic images for osteoporosis prediction could be effective.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.1017-1018
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• 2010

• Computers and Concrete
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• v.21 no.6
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• pp.727-739
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• 2018

Crack is the most common typical feature of concrete deterioration, so routine monitoring and health assessment become essential for identifying failures and to set up an appropriate rehabilitation strategy in order to extend the service life of concrete structures. At present, image segmentation algorithms have been applied to crack analysis based on inspection images of concrete structures. The results of crack segmentation offering crack information, including length, width, and area is helpful to assist inspectors in surface inspection of concrete structures. This study proposed an algorithm of image segmentation enhancement, named morphological segmentation based on edge detection-II (MSED-II), to concrete crack segmentation. Several concrete pavement and building surfaces were imaged as the study materials. In addition, morphological operations followed by cross-curvature evaluation (CCE), an image segmentation technique of linear patterns, were also tested to evaluate their performance in concrete crack segmentation. The result indicates that MSED-II compared to CCE can lead to better quality of concrete crack segmentation. The least area, length, and width measurement errors of the concrete cracks are 5.68%, 0.23%, and 0.00%, respectively, that proves MSED-II effective for automatic measurement of concrete cracks.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.227-233
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• 2017

Purpose: Morphological properties of soybean roots are important indicators of the vigor of the seed, which determines the survival rate of the seedlings grown. The current vigor test for soybean seeds is manual measurement with the human eye. This study describes an application of a machine vision technique for rapid measurement of soybean seed vigor to replace the time-consuming and labor-intensive conventional method. Methods: A CCD camera was used to obtain color images of seeds during germination. Image processing techniques were used to obtain root segmentation. The various morphological parameters, such as primary root length, total root length, total surface area, average diameter, and branching points of roots were calculated from a root skeleton image using a customized pixel-based image processing algorithm. Results: The measurement accuracy of the machine vision system ranged from 92.6% to 98.8%, with accuracies of 96.2% for primary root length and 96.4% for total root length, compared to manual measurement. The correlation coefficient for each measurement was 0.999 with a standard error of prediction of 1.16 mm for primary root length and 0.97 mm for total root length. Conclusions: The developed machine vision system showed good performance for the morphological measurement of soybean roots. This image analysis algorithm, combined with a simple color camera, can be used as an alternative to the conventional seed vigor test method.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.727-734
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• 2002

Currently. people become interested in the development of measuring instrument related to eyesight. In this study, we developed software of electronic part in automatic refracto-keratometer. If an automatic system, which uses images from an optical instrument, can inform the in-spector of an accurate eyesight measured value after the internal process, the frequency of mistakenly observed value will be reduced considerably. This software is using morphological filtering and gray-level signal enhancing techniques. The morphological filtering is the first process, from images of the optical instrument, to transform an original image which is hard to process into manageable one. The second process is a signal enhancing technique to the first processed image using gray -level thresholding technique and is used to reduce an error caused by the variety in distribution of the gray value of image. Therefore, this software system in electronic part will make more effective eyesight measurement by reducing the error effectively when applied to the optical image which is difficult to get accurate measurement value.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.4
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• pp.469-478
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• 2012

To manage, sort, and grade fishery resources, it is necessary to measure their morphometric characteristics. This labor-intensive task involves performing repetitive operations on land and on a research vessel. To reduce the amount of labor required, a vision-based automatic measurement system (VAMS) for the measurement of morphometric characteristics of flatfish, such as total length (TL), body width (BW), and body height (BH), has been developed as part of a database management system for fishery resources management. This system can also measure the mass (M) of flatfish. In the present study, we describe a morphological image processing algorithm for the measurement of certain characteristics of flatfish. This algorithm, which involves preprocessing, edge pattern matching, and edge point detection, is effective in cases where the flatfish being measured has a deformed tail and is randomly oriented. The satisfactory performance of the proposed algorithm is also demonstrated by means of experiments involving the measurement of the BW, TL and BH of a flatfish when it is straightened (BW : 117mm, TL : 329mm, BH : 24.5mm), when its tail is deformed, and when it is randomly oriented.

• Journal of Ecology and Environment
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• v.30 no.2
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• pp.195-199
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• 2007

Statistical tools for determining sex in the sexually monomorphic black-billed magpie based on morphological characters have been developed based on studies of European and North American populations. However, since no morphological method has been developed for black-billed magpies in Korea, it has been difficult to conduct field studies that require information about the sex of individuals. We present two discriminant equations for determining sex of second-year (SY) and after-second-year (ASY) magpies in north- and midwestern part of South Korea. Based on morphological measurements on 105 SY (56 females, 49 males) and 72 ASY (36 females, 36 males) individuals, we found body mass, wing chord, and head length to be the most useful features for morphological sex determination. The accuracy of our method was 86.5% for SYs and 93.1% for ASYs, which is similar to values reported previously from American and European magpies. Since the equations contain morphological traits which are only minimally susceptible to seasonal variation and measurement errors, our discriminant equations should be both useful and robust for sex determination on black-billed magpies in the northern and mid-western regions of South Korea.

• Journal of ILASS-Korea
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• v.7 no.4
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• pp.23-31
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• 2002

In this study, the sizes and velocities of droplets in sprays were measured by image processing method from digital images of local region of sprays. The morphological method based on the Euclidean distance transform, Watershed separation, and perimeter image was adopted for the recognition and separation of overlapped particles. The match probability method was used for the particle tracking and pairing. The measurement results show that the present method may be reliable for the analysis of the motion and distribution of droplets produced by spray and atomization devices.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.