• International Journal of Advanced Culture Technology
• /
• v.7 no.1
• /
• pp.64-69
• /
• 2019

With the advent of the fourth industry, the need for office automation with automatic character recognition capabilities is increasing day by day. Therefore, in this paper, we study a character recognition algorithm that effectively recognizes a new experimental data character by using learning data characters. The proposed algorithm computes the degree of similarity that the structural regions of learning data characters match the corresponding regions of the experimental data character. It has been confirmed that satisfactory results can be obtained by selecting the learning data character with the highest degree of similarity in the matching process as the final recognition result for a given experimental data character.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.2E
• /
• pp.8-13
• /
• 2000

In this paper, we present an adaptive formant tracking algorithm for speech using closed phase WRLS-VFF-VT method. The pitch synchronous closed phase methods is known to give more accurate estimates of the vocal tract parameters than the pitch asynchronous method. However the use of a pitch-synchronous closed phase analysis method has been limited due to difficulties associated with the task of accurately isolating the closed phase region in successive periods of speech. Therefore we have implemented the pitch synchronous closed phase WRLS-VFF-VT algorithm for speech analysis, especially for formant tracking. The proposed algorithm with the variable threshold(VT) can provide a superior performance in the boundary of phone and voiced/unvoiced sound. The proposed method is experimentally compared with the other method such as two channel CPC method by using synthetic waveform and real speech data. From the experimental results, we found that the block data processing techniques, such as the two-channel CPC, gave reasonable estimates of the formant/antiformant. However, the data windows used by these methods included the effects of the periodic excitation pulses, which affected the accuracy of the estimated formants. On the other hand the proposed WRLS-VFF-VT method, which eliminated the influence of the pulse excitation by using an input estimation as part of the algorithm, gave very accurate formant/bandwidth estimates and good spectral matching.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.553-559
• /
• 2004

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

• Journal of Korean Society for Geospatial Information Science
• /
• v.7 no.2 s.14
• /
• pp.47-56
• /
• 1999

In this study, tie point observation in aerial triangulation was automated by the image processing methods. The technique includes boundary extraction and We matching processes. The procedures were applied to extract points of Interest and to find their conjugate points in the other images. The image coordinates of the identified points were then used to compute their absolute coordinates. An algorithm was developed in this study for the automation of observation in aerial triangulation, which is a manual process of selecting a tie point and recording the image coordinate of the selected point. The developed algorithm automates this process through the application of a mathematical operator to extract points of interest from an arbitrary image. The root m square error of image coordinates of the developed algorithm is $6.8{\mu}m$, which is close to that of the present analytical method. In a manual environment, the accuracy of the result of a photogrammetric process is heavily dependant on the level of skill and experience of the human operator. No such problem exists in an automated system. Also, as a result of the automated system, the time spent in the observation process could be reduced by a factor of 61.2%, thereby reducing the overall cost.

• Journal of IKEEE
• /
• v.9 no.1 s.16
• /
• pp.19-30
• /
• 2005

Packet classification is defined as the action to match the packet with a set of predefined rules. One of classification is to use Ternary Content Addressable Memory hardware search engine that has faster than other algorithmic methods. However, TCAM has some limitations. One of them is that TCAM can not perform range matching efficiently. A range has to be expanded into prefixes to fit the boundary. In general, the number of expansion could be up to 2w-2, where w is the width of the field. For example, if two range fields with 16 bits are used, there could be up to $30\;{\times}\;30\;=\;900$ expansions for a single rule. In this paper, we describe the novel algorithm for converting range matching rules into TCAM entry efficiently. The number of maximum entry is 2w-4 when using the algorithm. Furthermore, it has also benefit about the negation range. In the result of experimentation, the new scheme practically reduces 14 percent in case that searched fields are source port and destination port number.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.5
• /
• pp.134-140
• /
• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.11
• /
• pp.5419-5435
• /
• 2017

The construction of panoramic images on smartphones and low-powered devices is a challenging task. In this paper, we propose a new approach for smoothly stitching images on mobile phones in the presence of moving objects in the scene. Our main contributions include handling moving object problems, reducing processing time, and generating rectangular panoramic images. First, unique and robust feature points are extracted using fast ORB method and a feature matching technique is applied to match the extracted feature points. After obtaining good matched feature points, we employ the non-deterministic RANSAC algorithm to discard wrong matches, and the hommography transformation matrix parameters are estimated with the algorithm. Afterward, we determine precise overlap regions of neighboring images and calculate their absolute differences. Then, thresholding operation and noise removal filtering are applied to create a mask of possible moving object regions. Sequentially, an optimal seam is estimated using dynamic programming algorithm, and a combination of linear blending with the mask information is applied to avoid seam transition and ghosting artifacts. Finally, image-cropping operation is utilized to obtain a rectangular boundary image from the stitched image. Experiments demonstrate that our method is able to produce panoramic images quickly despite the existence of moving objects.

• Journal of Korea Multimedia Society
• /
• v.7 no.11
• /
• pp.1531-1539
• /
• 2004

In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

• Coupled systems mechanics
• /
• v.4 no.3
• /
• pp.263-277
• /
• 2015

This paper presents a coupled FEM-BEM strategy for the numerical analysis of elastodynamic problems where infinite-domain models and complex heterogeneous media are involved, rendering a configuration in which neither the Finite Element Method (FEM) nor the Boundary Element Method (BEM) is most appropriate for the numerical analysis. In this case, the coupling of these methodologies is recommended, allowing exploring their respective advantages. Here, frequency domain analyses are focused and an iterative FEM-BEM coupling technique is considered. In this iterative coupling, each sub-domain of the model is solved separately, and the variables at the common interfaces are iteratively updated, until convergence is achieved. A relaxation parameter is introduced into the coupling algorithm and an expression for its optimal value is deduced. The iterative FEM-BEM coupling technique allows independent discretizations to be efficiently employed for both finite and boundary element methods, without any requirement of matching nodes at the common interfaces. In addition, it leads to smaller and better-conditioned systems of equations (different solvers, suitable for each sub-domain, may be employed), which do not need to be treated (inverted, triangularized etc.) at each iterative step, providing an accurate and efficient methodology.

• The KIPS Transactions:PartB
• /
• v.12B no.7 s.103
• /
• pp.755-760
• /
• 2005

To transmit a video bit stream over low bandwith, such as mobile, channels, encoding algorithms for high bit rate like H.263+ are used. In transmitting video bit-streams, packet losses cause severe degradation in image quality. This paper proposes a new algorithm for the recovery of missing or erroneous motion vectors when H.263+ bit-stream is transmitted. Considering that the missing or erroneous motion vectors are closely related with those of neighboring blocks, this paper proposes a temporal-spatial error concealment algorithm. The proposed approach is that missing or erroneous Motion Vectors(MVs) are recovered by clustering the movements of neighboring blocks by their homogeneity. MVs of neighboring blocks we clustered according to ALA(Average Linkage Algorithm) clustering and a representative value for each cluster is determined to obtain the candidate MV set. By computing the distortion of the candidates, a MV with the minimum distortion is selected. Experimental results show that the proposed algorithm exhibits better performance in subjective and objective evaluation than existing methods.