경찰공무원의 재난관리역량 제고를 위한 영향요인 분석

정수웅,민흥기 한국치안행정학회 2025 한국치안행정논집 Vol.22 No.1

이 연구는 현대사회가 겪고 있는 다양한 재난과 위기 상황에 대응하여야 하는 경찰공무원들이, 그 역량을 강화함에 있어 어떠한 요인들이 작용할 수 있는지를 검증한 선행연구들이 부족하다는 문제의식에서 시작되었다. 재난 발생 시 초기 대응의 핵심 주체로서 중요한 역할을 담당하는 경찰공무원이 효과적인 재난 대응능력을 보이기 위해서는 소속된 부서의 의사소통이나 팀워크라는 조직적 차원, 그리고 체계적인 교육 훈련이라는 교육적 차원이 담보되어야 할 것이다. 이에 따라 이 연구는 조직차원 및 교육차원의 변인들을 주요 요인으로 설정하여 경찰공무원의 재난대응역량에 미치는 영향을 규명하고, 그 영향관계에서 직무만족이 갖는 매개효과를 검증함으로써 경찰공무원의 재난대응 역량 강화를 위한 구체적인 정책적, 실천적 방안을 제안하는 것을 그 목적으로 하였다. 분석결과, 독립변수와 매개변수 간의 회귀모형에서는 팀워크와 의사소통이, 독립변수 및 매개변수와 종속변수 간의 회귀모형에서는 팀워크와 교육훈련체제, 그리고 직무 만족이 통계적으로 유의미한 영향력을 갖는 것으로 확인되었다. 이 독립변수와 종속변수 간의 영향관계에서 직무만족의 매개효과를 검증한 결과, 의사소통과 팀워크에 대해서는 유의한 간접효과를 갖지만, 교육훈련체계에 대해서는 간접효과를 보이지 못하는 것으로 나타났다. 이 연구의 주요 결과는 경찰공무원의 재난대응역량 강화에 있어 두 가지 차원의 접근이 필요함을 시사한다. 기본적으로는 재난대응과 관련한 교육훈련체제가 제대로 완비될수록 재난대응역량이 증가하므로 교육적 측면이 강화되어야 한다는 것이고, 추가적으로 경찰공무원이 소속된 부서의 팀워크와 의사소통의 정도가 직무만족을 경유하여 재난대응역량을 또한 증대시킬 수 있기에 조직적 측면에서도 접근 가능하다는 것이다. 이를 토대로 조직관리라는 측면이 단순히 운영의 효율성 증대만이 아닌 업무의 효과성에도 영향을 미칠 수 있기에 재난대응역량을 증진함에 있어 직무훈련만이 아닌 조직관리적 차원도 고려해야 한다는 정책적 제언을 실시하였다. This study began with the awareness of the problem that there is a lack of previous studies that verified what factors can be at work in strengthening the capabilities of police officers who must respond to various disasters and crisis situations experienced in modern society. In order for police officers, who play an important role as key players in the initial response in the event of a disaster, to demonstrate effective disaster response capabilities, organizational dimensions such as communication and teamwork within the department to which they belong, and educational dimensions such as systematic education and training must be secured. Accordingly, this study aimed to identify the influence of organizational and educational variables on the disaster response capabilities of police officers by setting them as major factors and verifying the mediating effect of job satisfaction in the influence relationship. In addition, it aimed to propose specific policy and practical measures to strengthen the disaster response capabilities of police officers. As a result of the analysis, teamwork and communication were confirmed to have a statistically significant influence in the regression model between independent variables and mediators, and teamwork, education and training system, and job satisfaction were confirmed to have a statistically significant influence in the regression model between independent variables, mediators, and dependent variables. Meanwhile, the results of verifying the mediating effect of job satisfaction in the relationship between the independent and dependent variables showed that it had a significant indirect effect on communication and teamwork, but did not show an indirect effect on the education and training system. The main results of this study, as mentioned above, suggest that a two-dimensional approach is necessary to strengthen the disaster response capabilities of police officers. Basically, the more the education and training system related to disaster response is properly completed, the more disaster response capabilities increase, so the educational aspect should be strengthened. In addition, the level of teamwork and communication in the department to which police officers belong can also increase disaster response capabilities through job satisfaction, so it can be approached from an organizational perspective. Based on this, the organizational management aspect can affect not only the efficiency of operation but also the effectiveness of work, so a policy suggestion was made that not only job training but also the organizational management dimension should be considered when enhancing disaster response capabilities.

은닉 마르코프 모델을 이용한 온라인 숫자 인식에 관한 연구

정수웅 김천과학대학 1996 김천과학대학 논문집 Vol.22 No.-

In this paper, an on-line recognition system of hand-written number is presented. The recognition of handwritten number has a difficulty of grapheme segmentation and a complexity in matching process due to the incrreasing number of candidates. To deal with these problem, we propose an automatic number recognition using hidden markov model.

실시간 비디오 감시에서 신경망 기반의 얼굴 검출

정수웅 김천과학대학 2003 김천과학대학 논문집 Vol.29 No.-

본 논문에서는 실시간 비디오 감시 시스템에서 움직이는 사람들의 얼굴을 추출하고 추적하는 방법을 제안한다. 얼굴 추출 과정에서 계산량으로 인한 부하를 줄이기 위해 제안한 방법은 변화 영역 접근 방식에 기반을 두고 있다. 전체적인 얼굴 추출 방법은 두 단계로 구성되어 있다. 첫 번째 단계는 움직이는 영역 추출을 위해 자동으로 임계값을 선택하는 적응 임계치 방법을 사용한다. 그리고, 임계 처리된 영상에서 이진 모션 마스크들을 생성한다. 두 번째 단계에서는 얼굴 영역을 검출한다. 얼굴 영역 추출은 추출된 모션 마스크 내에서 미리 정의된 피부색 모델을 활용하여 유사한 피부색을 가지는 픽셀들이 추출되고 후보 얼굴 영역들이 얻어진다. 후보 얼굴 영역들에 대해 얼굴의 크기와 모양을 학습한 신경망에 적용하여 실제 얼굴을 검출한다. 현재 프레임에서 검출된 얼굴을 바탕으로 연속된 프레임에서 얼굴들이 추적된다. 실험을 통하여 제안한 방법이 잡음이나 배경이 복잡한 영상에서 매우 효과적으로 얼굴을 추출함을 보인다. In this paper, we present a method to track and detect faces of moving humans for real-time video surveillance. In order to reduce the computational load to the human face detection, the presented method is based on the variation regions application. The method consists of two steps: moving region detection and face region detection. First, the moving region detection, the rough positions of moving objects in image sequence are determined using an adaptive thresholding method that automatically choose the threshold value for detecting the moving regions. Then, we obtained binary motion masks. Second, the face region detection, the pixels in the detected motion masks that have similar skin-color are extracted using the predefined skin-color model, which is a stochastic model to characterize skin-colors of human faces, then we obtain the binary candidate face region masks. The candidate face regions are classified into the real face region using neural network, which is trained size and shape of face. Based on the detected face in current frame, faces are tracked in consecutive frames. Our experimental results show that the presented method is robust under complex background and some noise.

On-Line 한글 인식을 위한 퍼지 이론의 이용에 관한 연구

정수웅 김천과학대학 1993 김천과학대학 논문집 Vol.19 No.-

In this paper, Using a Fuzzy theory an On-Line phoneme recognition procedure of Korean characters is studied. The recognition method is performed by reading the pixel coordinates, finding the frature points, recognizing the stroke, recognizing the phoneme in order. In the course of recognizing the stroke, First the frature points of an inputed stroke is characterized by starting point, end point, and bending point. Second, We investigate that The connection style between the former stroke and the latter stroke from the set of input strokes is related. And The relative direction between the former stroke and the latter stroke is considered. Finally, According to the above three form(stroke code, connection style, relative direction) We recognize a written korean character using finite automata.

영숫자 그림이 혼용된 한글문서에서 문자 분리에 관한 연구

정수웅,이갑래 김천과학대학 1998 김천과학대학 논문집 Vol.24 No.-

In this paper, we propose a new method for segmenting characters in hangul document mixed with alphanumeric characters and picture. Since hangul has structural characteristics different from those of alphanumeric characters, structural characteristics of hangul characters are also different from those of alphanumeric ones. If hangul and alphanumeric characters are both written in a document, it is difficult to know whether the touching characters are hangul or not. The proposed segmentation method uses an MLP to generate candidate cutting points. The MLP-based segment lea군 cutting points from training samples which are composed of features extracted from touching character images and correct cutting point of those images. It generates five candidate cutting points per a touching character image and each candidate has a value that is regarded as cutting possibility at that position.

복잡한 배경의 칼라 영상에서 허프 변환을 이용한 글자 영역 추출

정수웅 김천과학대학 2001 김천과학대학 논문집 Vol.27 No.-

An efficient method to extract text regions in complex color images is proposed. An algorithm locates the spatial position and estimates the skew of the text lines which are present in image using the local color information and hough transform. The color image is divided into sub-blocks. Sub-blocks are classified into a background block and a character candidate block by intensity variance and contrast. The background intensity is erased from 3×3 neighbor blocks. Similar blocks in hue and saturation are grouped into a region. Regions are refined by several heuristic parameters such as color, size and position information. Binary image is obtained after region refinement and is segmented into connected components. Character candidate components are detected by filtering noncharacter-like components based on several heuristics. The skew of the text lines are estimated by applying the hough transform. The proposed method have been used to locate text regions in book cover images. Experimental results are reported.

덕유산 황금빛 나무

정수웅,오민진(사진) 월간에세이 2019 (월간)에세이 Vol.381 No.-

자동 획 분류에 의한 온라인 흘림 필기 한자의 인식

정수웅 김천과학대학 1995 김천과학대학 논문집 Vol.21 No.-

In this paper, an on-line recognition system of hand-written chinese character is presented. The recognition of handwritten chinese character has a difficulty of grapheme segmentation and a complexity in matching process due to the incrreasing number of candidates. To deal with these problem, we propose an automatic stroke classification using neural network. Character recognition is done bt traversing chinese database with a sequence of recognized strokes and positional relations between the strokes. The database is dynamically constructed with generalized character lists and a character can be included simply by adding a new sequence to the list.

비디오 영상에서 SVM과 HMM을 사용한 얼굴영역 추출

정수웅 김천과학대학 2007 김천과학대학 논문집 Vol.33 No.-

In this paper, we present the method of detecting some face regions in video images using Support Vector Machine and Hidden Markov Model. Face images from a camera are mapped into a texture space and then, some texture informations are extracted in face images. Given texture informations, face regions are detected. For extracting some texture informations in face images, 10 Support Vector Machines are used. PCA(principle Component Analysis) is used to reduce dimension, and then a face pattern is obtained. The obtained pattern doesn't represent the entire image texture, but represent the pixel texture information. Accordingly the pattern represents a spacial distribution of each texture information. The detection of face regions is performed using HMM, which shows texture of input image and spatial characteristics of texture. In order to reduce the computational load to the human face detection, the presented method is based on the variation regions application. The method consists of two steps: moving region detection and face region detection. First, the moving region detection, the rough positions of moving objects in image sequence are determined using an adaptive thresholding method that automatically choose the threshold value for detecting the moving regions. Then, we obtained binary motion masks. Second, the face region detection, the pixels in the detected motion masks that have similar texture are extracted. Some candidate face regions are classified into real face regions using HMM. The experiment is showed that the presented method is robust to a motion-blur and saturated image under illumination variation.

HPC상에서 온라인 문자 인식 시스템

정수웅 김천과학대학 1997 김천과학대학 논문집 Vol.23 No.-

While significant advances have been made in recent years to improve handwritting recognition systems and Hand held PC(HPC), Korean character recognition systems on HPC have still not found broad acceptance in everyday life. In this paper, we present a recognition system of on-line cursive Korean character on HPC. Our system is constructed with hidden Markov model-based character recognition. Hidden Markov model is constructed with nodes for graphemes and edges for Korean combination rules.