• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.1-7
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• 2017

Clipart is artificial visual contents that are created using various tools such as Illustrator to highlight some information. Here, the style of the clipart plays a critical role in determining how it looks. However, previous studies on clipart are focused only on the object recognition [16], segmentation, and retrieval of clipart images using hand-craft image features. Recently, some clipart classification researches based on the style similarity using CNN have been proposed, however, they have used different CNN-models and experimented with different benchmark dataset so that it is very hard to compare their performances. This paper presents an experimental analysis of the clipart classification based on the style similarity with two well-known CNN-models (Inception Resnet V2 [13] and VGG-16 [14] and transfers learning with the same benchmark dataset (Microsoft Style Dataset 3.6K). From this experiment, we find out that the accuracy of Inception Resnet V2 is better than VGG for clipart style classification because of its deep nature and convolution map with various sizes in parallel. We also find out that the end-to-end training can improve the accuracy more than 20% in both CNN models.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.653-668
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• 2012

In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a post-processing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.322-327
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• 2005

In this paper we Propose a method that enables to recognize the laser stripe with 3dimensional information of body. Laser stripe has 3-dimensional information. We found out patterns of stripe have features of body. So we made database of it using Fourier Descriptor method and compared it with another stripe of body to recognize bodies. We could recognize standard style of body efficiently It is respected that deep research should be studied on the different style of bodies and then the other features of human will be recognized.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.23-30
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• 2005

As a human identification technique, gait recognition has recently gained significant attention. Silhouette-based gait recognition is one of the most popular methods. This paper aims to investigate features that determine the style of walking in silhouette-based gait recognition. Gait can be represented using two cues: static(shape) cue and dynamic(motion) cue. Most recently, research results have been reported in the literature that the characteristics of gait are mainly determined by static cue but not affected by dynamic cue. Unlike this, experimental results in this paper verifies that dynamic cue is as important as and in many cases more important than static cue. For experiments, we use two well-blown gait databases: UBC DB and Southampton Small DB. The images of UBC DB correspond to the 'ordinary' style of walking. The images of Southampton Small DB correspond to the 'disguised' (not ordinary by wearing special clothes or bags) style of walking. As results of experiments, the recognition rate was 100% by static cue and $95.2\%$ by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the recognition rate was $50.0\%$ by static cue and $55.8\%$ by dynamic cue. The risk against correct recognition was 0.91 by static cue and 0.97 by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the risk was 0.98 by static cue and 0.98 by dynamic cue. Consequently, the characteristics of ordinary gait are mainly determined by static cue but that of disguised gait by dynamic cue.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.39-42
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• 2017

Communication between human and machine is having been researched from last few decades and still it's a challenging task because human behavior is unpredictable. When it comes on handwritten digits almost each human has their own writing style. Handwritten digit recognition plays an important role, especially in the courtesy amounts on bank checks, postal code on mail address etc. In our study, we proposed an efficient feature extraction system for recognizing single digit number drawn by mouse or by a finger on a screen. Our proposed method combines basic image processing and reading the strokes of a line drawn. It is very simple and easy to implement in various platform as compare to the system which required high system configuration. This system has been designed, implemented, and tested successfully.

• The Journal of the Acoustical Society of Korea
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• v.24 no.2E
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• pp.67-70
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• 2005

To realize a traditional music recognition system, some characteristics pertinent to Far East Asian music should be found. Using Spectrogram, some distinct attributes of Korean traditional music are surveyed. Frequency distribution, beat cycle and frequency energy intensity within samples have distinct characteristics of their own. Experiment is done for pre-experimentation to realize Korean traditional music recognition system. Using characteristics of Korean traditional music, $94.5\%$ of classification accuracy is acquired. As Korea, Japan and China have the same musical roots, both in instruments and playing style, analyzing Korean traditional music can be helpful in the understanding of Far East Asian traditional music.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

• Korean Journal of Human Ecology
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• v.18 no.2
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• pp.465-476
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• 2009

The purpose of this study is to investigate recognition degree and acceptability of fashion trends of new consumers who live in digital era, and to determine how these factors have influence on their use of fashion trend information. The study was conducted with 696 people from 15 to 34 years old. A self-administrated questionnaire based on the results of previous researches was developed. The data were analyzed with statistical analyses such as frequency analysis, mean, factor analysis, t-test, ANOVA, correlation and regression analysis. The results are as follows: first, new digital consumer's recognition degree (RD) of fashion trends is 7.85 on the average, given that the top of scale is 20.0, it is quite low. Of fashion trend RD, fashion item RD is the highest. The female subjects recognize fashion trends better than the male subjects. Second, fashion trend acceptance of new digital generation is classified into 5 factors: 'search acceptance', 'lead acceptance', 'follow acceptance', 'non-acceptance', and 'delay acceptance'. The female subjects show higher degree in the factors of 'search acceptance', 'lead acceptance' and 'follow acceptance' of fashion trend than the males; hence it means that the females have more positive attitudes in fashion trend acceptance than the males. Third, there are significant differences between genders in the fashion information utilization. Compared to the males, the females more use fashion information on style, fabrics and color. Concludingly, their fashion trend recognition degree and acceptance made an influence in part on their utilization of fashion information.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.27-35
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• 1999

Researches on the recognition of handwritten script have been conducted under the assumption that the isolated recognition units are provided as inputs. However, in practical recognition system designs, providing the isolated recognition unit is an challenge due to various writing syles. This paper proposes an approach for segmenting words from lines of unconstrained handwritten text, without help of recognition. In contrast to the conventional approaches which are based on physical gaps between connected components, clues that reflect the author's writing style, in terms of spacing, are extracted and utilized for the segmentation using a simple neural network. The clues are from character segments and include normalized heights and intervals of the segments. Effectiveness of the proposed approach compared with the conventional connected component based approaches in terms of word segmentation performance was evaluated by experiments.