• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.539-541
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• 2005

We propose efficient video retrieval scheme which use fast key frame extraction in DCT domain. Our scheme extract key frame using the edge histogram difference which is extracted in compressed domain for I-frames. And the video retrieval is implemented using Hausdorff distance function about edge histogram of key frame. This approach enables fast content-based video retrieval of the compressed video content without decompression process. Experimental results show our scheme is very fast and efficient.

• Ocean Systems Engineering
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• v.2 no.2
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.339-345
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• 2021

The rapid development of various applications in networking system, business, medical, education, and other domains that use basic data access operations such as insert, edit, delete and search makes data structure venerable and crucial in providing an efficient method for day to day operations of those numerous applications. One of the major problems of those applications is achieving constant time to search a key from a collection. A number of different methods which attempt to achieve that have been discovered by researchers over the years with different performance behaviors. This work evaluated these methods, and found out that almost all the existing methods have non-constant time for adding and searching a key. In this work, we designed a multi-indexes hashing algorithm that handles a collision in a hash table T efficiently and achieved constant time O(1) for searching and adding a key. Our method employed two-level of hashing which uses pattern extraction h₁(key) and h₂(key). The second hash function h₂(key) is use for handling collision in T. Here, we eliminated the wasted slots in the search space T which is another problem associated with the existing methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.45-52
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• 2004

According tothe development of digital media technologies various algorithms for video sequence matching have been proposed to match the video sequences efficiently. A large number of video sequence matching methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video sequence matching or video shot matching. In this paper, we propose an efficientalgorithm to index the video sequences and to retrieve the sequences for video sequence query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous fames. Several key frame extraction algorithms have been proposed, in which similar methods used for shot boundary detection were employed with proper similarity measures. In this paper, we propose the efficient algorithm to extract key frames using the cumulative Cauchy function measure and. compare its performance with that of conventional algorithms. Video sequence matching can be performed by evaluating the similarity between data sets of key frames. To improve the matching efficiency with the set of extracted key frames we employ the Cauchy function and the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.141-149
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• 2003

As music of digital form has been widely used, many people have been interested in the automatic extraction of natural information of music itself, such as key of a music, chord progression, melody progression, tempo, etc. Although some studies have been tried, consistent and reliable results of musical information extraction had not been achieved. In this paper, we propose a method to extract chord and tempo information from general polyphonic music signals. Chord can be expressed by combination of some musical notes and those notes also consist of some frequency components individually. Thus, it is necessary to analyze the frequency components included in musical signal for the extraction of chord information. In this study, we utilize a sinusoidal modeling, which uses sinusoids corresponding to frequencies of musical tones, and show reliable chord extraction results of sinusoidal modeling. We could also find that the tempo of music, which is the one of remarkable feature of music signal, interactively supports the chord extraction idea, if used together. The proposed scheme of musical feature extraction is able to be used in many application fields, such as digital music services using queries of musical features, the operation of music database, and music players mounting chord displaying function, etc.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.59-64
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• 2013

Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

• Journal of IKEEE
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• v.22 no.4
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• pp.1019-1024
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• 2018

In this paper, we suggest a combined cost function to find out the optimal operation of an envelope tracking system, and evaluated its performance with Quadrature Amplitude Modulation (QAM) waveform, with which envelope tracking coefficients for the peak drain efficiency and the bandwidth of power amplifiers are determined. Based on the classical envelope tracking theory, the operation of the supply modulator, which is a key part of the envelope tracking process, is modeled and analyzed mathematically. Then characteristics of the modulator by setting envelope shaping function as a cubic polynomial and sweeping the coefficients of this function was analyzed. By sweeping the coefficients, efficiency and bandwidth at each condition with 64-QAM signal was used to obtain optimal point of the supply modulator. Compared to the conventional shaping functions, the optimized function showed the bandwidth reduction by 12.7 percent point while the efficiency was maintained.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.717-738
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• 2017

Purpose: This study focused on procedure and methodology for finding the critical design factors in the early stage of product development process. Methods: Firstly, three key criteria, function, affection and usability were defined as the determining factors on customer satisfaction. Secondly, evaluation matrix in terms of each key criteria was proposed for extraction of the critical design factors. Lastly, method of integrating the importance among three key criteria was suggested using structured equation model. Results: As a results of integrating the importance, design factors such as touch sensitiveness and touch method were rated as low in terms of affection. However, these factors were obtained for high ratings with respect to functionality and usability. Thus, touch-related design factors were more facilitated for enhancing customer satisfaction. Conclusion: It is expected that the process suggested in this research could be a considerably useful to maximize customer satisfaction in the early stage of product development process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.560-574
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• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.