• Parasites, Hosts and Diseases
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• v.48 no.3
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• pp.253-257
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• 2010

Two adult rock partridges raised in a city zoo were examined parasitologically and pathologically. Two distinctive eggs resembling those of Capillaria and Heterakis were detected in the feces. At necropsy, a markedly-dilated duodenum with severe catarrhal exudates, containing adult worms of Capillaria sp. and Heterakis sp. in the cecum, was observed. Male Capillaria had the cloacal aperture extended almost terminally with a small bursal lobe and an unsheathed spicule with transverse folds without spines. Female Capillaria had a vulva that was slightly prominent and slightly posterior to the union of the esophagus and intestine. The esophagus of the adult Capillaria was more than a half as long as the body in the male, but was much shorter in the female. Based on these morphological features, the capillarid nematode was identified as Capillaria obsignata. The male adult worms of Heterakis was identifiable by 2 dissimilar spicules, a unique morphological feature where the right spicule was considerably longer than the left, which is also a characteristic feature of Heterakis gallinarum. This is the first report of concurrent infections with C. obsignata and H. gallinarium in rock partridges.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.197-200
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• 1995

In this paper, we proposed the multi-step multi-layer artificial neural network(MMANN) to classify the chromosome, Which is used as a chromosome pattern classifier after learning. We extracted three chromosome morphological feature parameters such as centromeric index, relative length ratio, and relative area ratio by means of preprocessing method from ten chromosome images. The feature parameters of five chromosome images were used to learn neural network and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more, comparing with less feature parameters than that of the other researchers.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.7-12
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• 2009

In this paper, we propose a directional feature extraction method for off-line handwritten numerals by using the morphological operations. Direction features are obtained from four directional line images, each of which contains horizontal, vertical, right-diagonal and left-diagonal lines in entire numeral lines. Conventional method for extracting directional features uses Kirsch masks which generate edge-shaped double line images for each direction, whereas our method uses directional erosion operations and generate single line images for each direction. To apply these directional erosion operations to the numeral image, preprocessing steps such as thinning and dilation are required, but resultant directional lines are more similar to numeral lines themselves. Our four [$4{\times}4$] directional features of a numeral are obtained from four directional line images through a zoning method. For obtaining the higher recognition rates of the handwrittern numerals, we use the multiple feature which is comprised of our proposed feature and the conventional features of a kirsch directional feature and a concavity feature. For recognition test with given features, we use a multi-layer perceptron neural network classifier which is trained with the back propagation algorithm. Through the experiments with the CENPARMI numeral database of Concordia University, we have achieved a recognition rate of 98.35%.

• 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.

• (The)Study of the Eastern Classic
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• no.41
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• pp.407-444
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• 2010

So far, we morphologically considered which satirized society in the enlightenment period. For this, we first looked into the feature of expletive and then analyzed it centering around Declension. At last, we conclude this subject with argument of the creation time of from the morphological analysis result. Begining with the conclusion, I thought that the origin opinion of the creation time of is right. In priority research focusing on people who major in literature, the creation time of is about 1901 to 1907, and it coincide with the result from morphological consideration of this article. First, at the feature of expletive, the advent of '~ 할 말이면' the expression of the conditional mood helped to estimate the creation time of . Prior literature of the creation time of (around 1910), '~ 작시면' is the corresponding conditional mood expression. but in the new-style fiction around , it change to '~ 말이면' and thereafter '~ 것 갓흐면' or '~' which seems similar to present korean. I analized the record for the feature of expletive. By dividing up with merce miswrite and miswrite from ignorance, we can assume that the Scripter of is not the fictionist. At the feature of declension, the full use of the nominative case marker '-가' was recordable. '-가' had already appeared in early modern korean, but until 1883 '-ㅣ' almost replaced it. However, around period, we could know that '-ㅣ' barely used and mostly use '-가'. From this, I estimated the creation time of is at least after 1883. In conclusion, I want to suggest an opinion that 1900 is proper sectioning time when we divide history of korean to Modern and Present korean based on the discussion of this article.

• Journal of Welding and Joining
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• v.31 no.5
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.179-199
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• 2019

In this paper, we propose optimal methodologies for classifying patent literature by examining various feature extraction methods, machine learning and deep learning models, and provide optimal performance through experiments. We compared the traditional BoW method and a distributed representation method (word embedding vector) as a feature extraction, and compared the morphological analysis and multi gram as the method of constructing the document collection. In addition, classification performance was verified using traditional machine learning model and deep learning model. Experimental results show that the best performance is achieved when we apply the deep learning model with distributed representation and morphological analysis based feature extraction. In Section, Class and Subclass classification experiments, We improved the performance by 5.71%, 18.84% and 21.53%, respectively, compared with traditional classification methods.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.52 no.2
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• pp.103-110
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• 2016

This study aims to estimate the species, size and shape of fish using a non-contact 3 dimensional pattern laser so that this preliminary test was carried out to understand the structural feature and length of goldfish according to water turbidity and depth in the aquacultural tank. 3-D pattern laser could clearly detect its morphological shape except the caudal fin due to soft tissue. Since the sensing strength of line laser light according to depth has sufficient power, it is possible to measure its depth and structural feature in the detected range. The result showed that the measured error of individual's fork length was less than ${\pm}1%$ in the water using 3-D pattern laser, when compared with the measured value in the air.

• ETRI Journal
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• v.38 no.1
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• pp.174-184
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• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.176-181
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• 2023

During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.