• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.751-760
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• 2009

This research aims to develop the strategy and method to enhance the reliability of image matching results and improve the efficiency of the matching process by utilizing LIDAR data in the main image matching processes. In this work, we present the methods to utilize LIDAR data in the selection of matching entities, the search for the matched entities and the evaluation of the matching results. The proposed method has been applied to medium-resolution digital aerial images and LIDAR data acquired at the same time. The results have been analyzed in comparison with an existing method using a virtual horizontal surface rather than LIDAR DEM. This analysis indicates that the proposed method can show significantly more improved performance than the existing method. The results of this study can contribute to the improvement of the currently available commercial image matching software and the enhancement of the DEM derived from LIDAR data and matching results.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.25-33
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• 2006

For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

• Radiation Oncology Journal
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• v.37 no.2
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• pp.134-142
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• 2019

Purpose: The aim is to study the dependence of deformable based auto-segmentation of head and neck organs-at-risks (OAR) on anatomy matching for a single atlas based system and generate an acceptable set of contours. Methods: A sample of ten patients in neutral neck position and three atlas sets consisting of ten patients each in different head and neck positions were utilized to generate three scenarios representing poor, average and perfect anatomy matching respectively and auto-segmentation was carried out for each scenario. Brainstem, larynx, mandible, cervical oesophagus, oral cavity, pharyngeal muscles, parotids, spinal cord, and trachea were the structures selected for the study. Automatic and oncologist reference contours were compared using the dice similarity index (DSI), Hausdroff distance and variation in the centre of mass (COM). Results: The mean DSI scores for brainstem was good irrespective of the anatomy matching scenarios. The scores for mandible, oral cavity, larynx, parotids, spinal cord, and trachea were unacceptable with poor matching but improved with enhanced bony matching whereas cervical oesophagus and pharyngeal muscles had less than acceptable scores for even perfect matching scenario. HD value and variation in COM decreased with better matching for all the structures. Conclusion: Improved anatomy matching resulted in better segmentation. At least a similar setup can help generate an acceptable set of automatic contours in systems employing single atlas method. Automatic contours from average matching scenario were acceptable for most structures. Importance should be given to head and neck position during atlas generation for a single atlas based system.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.356-367
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• 2008

As XML is gaining unqualified success in being adopted as a universal data representation and exchange format, particularly in the World Wide Web, the problem of querying XML documents poses interesting challenges to database researcher. Several structural XML query processing methods, including XISS and XR-tree, for past years, have been proposed for fast query processing. However, structural XML query processing has the problem of requiring expensive Join cost for twig path query Recently, sequence matching based XML query processing methods, including ViST and PRIX, have been proposed to solve the problem of structural XML query processing methods. Through sequence matching based XML query processing methods match structured queries against structured data as a whole without breaking down the queries into sub queries of paths or nodes and relying on join operations to combine their results. However, determining the structural relationship of ViST is incorrect because its numbering scheme is not optimized. And PRIX requires many processing time for matching LPS and NPS about XML data trees and queries. Therefore, in this paper, we propose efficient sequence matching method u sing the bottom-up query processing for efficient XML query processing. Also, to verify the superiority of our index structure, we compare our sequence matching method with ViST and PRIX in terms of query processing with linear path or twig path including wild-card('*' and '//').

• Convergence Security Journal
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• v.13 no.3
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• pp.9-15
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• 2013

Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1718-1734
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• 2012

The proposed method in this paper is derived from Mielikainen's hiding method. However, there exist some significant differences between two methods. In Mielikainen's method, pixels are partitioned into pairs and a LSB matching function is applied to two pixels for hiding. On the contrary, the proposed method partitions pixels into groups with three pixels in each group. The bits of pixels in each group are linked by using an exclusive OR (XOR) operator in a circular way. If the number of different values between the calculated XOR values and the secret bits is smaller than or equal to 2 in a group, the proposed method can guarantee that at most one pixel is needed to be modified by adding/subtracting its value to/from one, and three secret bits can be embedded to three pixels. Through theoretical analysis, the amount of the embedded secret data in the proposed method is larger than those in other methods under the same amount of pixel modifications. Taking real images in our experiments, the quality of stego-images in the proposed method is higher than those in other methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.130-137
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• 1992

This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.835-844
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• 2002

For the one-way random model when the ratio of the variance components is of interest, Bayesian analysis is often appropriate. In this paper, we develop the noninformative priors for the ratio of the variance components under the balanced one-way random effect model. We reveal that the second order matching prior matches alternative coverage probabilities up to the second order (Mukerjee and Reid, 1999) and is a HPD(Highest Posterior Density) matching prior. It turns out that among all of the reference priors, the only one reference prior (one-at-a-time reference prior) satisfies a second order matching criterion. Finally we show that one-at-a-time reference prior produces confidence sets with expected length shorter than the other reference priors and Cox and Reid (1987) adjustment.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.3
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• pp.293-300
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• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.