Parametric B-Spline 함수를 이용한 방향성 보간 ( Directional Interpolation Using Parametric B-spline Function )

이응주,김순자,하영호 대한전자공학회 1991 대한전자공학회 학술대회 Vol.1991 No.1

미리보는 2017년 에너지 산업 - 2017년 석유산업 경영환경 전망

이응주,Lee, Eung-Ju 대한석유협회 2017 석유와 에너지 Vol.302 No.-

정유년이 밝았다. 그러나 희망찬 새해 운운하기에는 대내외적 불확실성이 너무 크다. 촛불로 대표되는 국내 정치 여건의 급박한 변화 가능성, 미국 대통령 교체가 상징하는 국제 정치/경제 환경의 불안정성을 모두 고려해야 한다. 석유 산업은 더욱 큰 불확실성에 직면할 전망이다. OPEC 감산과 트럼프의 새로운 에너지 정책이라는 불협화음이 어떤 결과를 낳을지 쉽게 예단할 수 없다. 2017년 석유 산업이 처할 환경에 대해 조심스럽게 전망하고자 한다.

Face Recognition Based on Improved Fuzzy RBF Neural Network for Smart Device

이응주 한국멀티미디어학회 2013 멀티미디어학회논문지 Vol.16 No.11

Face recognition is a science of automatically identifying individuals based their unique facial features. In order to avoid overfitting and reduce the computational reduce the computational burden, a new face recognition algorithm using PCA-fisher linear discriminant (PCA-FLD) and fuzzy radial basis function neural network (RBFNN) is proposed in this paper. First, face features are extracted by the principal component analysis (PCA) method. Then, the extracted features are further processed by the Fisher's linear discriminant technique to acquire lower-dimensional discriminant patterns, the processed features will be considered as the input of the fuzzy RBFNN. As a widely applied algorithm in fuzzy RBF neural network, BP learning algorithm has the low rate of convergence, therefore, an improved learning algorithm based on Levenberg-Marquart (L-M) for fuzzy RBF neural network is introduced in this paper, which combined the Gradient Descent algorithm with the Gauss-Newton algorithm. Experimental results on the ORL face database demonstrate that the proposed algorithm has satisfactory performance and high recognition rate.

영상처리 기법을 이용한 실시간 섬유 성량 검사 시스템 개발

이응주,배성호,Lee, Eung-Ju,Bae, Seong-Ho 한국정보처리학회 2000 정보처리논문지 Vol.7 No.3

Textile dimension inspection is one of the basic issues in the textile dyeing and finishing industry. And also, it a plays an important role in the quality control of total fabric products. In this paper, we implement a real-time textile dimension inspection system which detects various real defects, defects positions of textile and the density of textiles. The proposed method consists of textile density measurement algorithms with zone-occurrence features from subband image which detect various types of real defects. The performance of the proposed method is tested with a number of real textile samples with 10 types of defects and three basic structures of textile. By the dimension inspection of textile at continuous stages in the fabrication process, it is possible to measure the density of textile up to 150m/min and to detect the defect of textile at real time within $\pm$1% error percentages. And also it can be monitored the condition of textile throughout at all the significant working process and can be improved textile quality.

적응적 얼굴검출 및 얼굴 특징자 평가함수를 사용한 실시간 얼굴인식 알고리즘

이응주,김정훈,김지홍 한국멀티미디어학회 2004 멀티미디어학회논문지 Vol.7 No.2

본 논문에서는 적응적 얼굴영역 검출과 얼굴 특징자 평가함수를 사용한 실시간 얼굴인식 알고리즘을 제안하였다. 제안한 알고리즘은 명암도 정보와 타원마스킹 기법뿐만 아니라 인종별 얼굴피부색을 사용하여 정확한 얼굴영역을 적응적으로 검출 가능하다. 또한 제안한 알고리즘은 얼굴 특징자 및 얼굴특징자간 기하학적 평가함수를 사용하여 얼굴 인식 효율을 개선하였다. 제안한 알고리즘은 생체인증 및 보안 시스템 분야에 사용 가능하다. 실험에서는 제안한 방법의 우수성을 입증하기 위해 실 영상을 사용하였으며 실험 결과 기존의 방법보다 얼굴 영역 검출뿐만 아니라 얼굴인식 성능을 개선하였다. In this paper, we propose an adaptive face region detection and real-time face identification algorithm using face feature evaluation function. The proposed algorithm can detect exact face region adaptively by using skin color information for races as well as intensity and elliptical masking method. And also, it improves face recognition efficiency using geometrical face feature and geometric evaluation function between features. The proposed algorithm can be used for the development of biometric and security system areas. In the experiment, the superiority of the proposed method has been tested using real image, the proposed algorithm shows more improved recognition efficiency as well as face region detection efficiency than conventional method.

색채 응용 시스템의 색향상을 위한 기호색 보정

이응주,하영호 한국통신학회 1997 韓國通信學會論文誌 Vol.22 No.7

In this paper, we propose a favorite color correction algorithm for color enhancement in color application system which represent preferred colors for viewer's demands. The proposed algorithm corrects skin color which is widely used as a reference color for color control of color application system, blue color which is directly related to tri-stimulus values, and green color which has higher visual sensitivity. In the proposed algorithm, the vaiation range of phase detector output voltage was minimized for the favorite color saturation changes, thus the favorite from the burst signal for the phase detector characteristic, thus the favorite color was easilty detected from the other color without overlapping of correctionranges.

섬유 제작 공정에서 실린더 렌즈를 이용한 섬유 검사 시스템 ( Texture Inspection System Using Cylindrical Lens in Texture Fabrication Process )

이응주,현기호 대한전자공학회 1997 대한전자공학회 학술대회 Vol.1997 No.1

고속의 직물 제직 공정에서 광학적 렌즈를 이용한 자동 밀도 측정 시스템

이응주,현기호,정인갑,Lee, Eung-Joo,Hyun, Eung-Joo,Jeong, In-Gab 한국정보처리학회 1998 정보처리논문지 Vol.5 No.1

The density of fabric is a very important parameter in many fabric production processes. However, in the textile fabrication factories, textile density measurement process has been done inefficiently by handicraft. Thus, exact textile density measurement process is necessary to fabricate high quality textile through weft straighten. In this paper, we propose an automatic textile density measurement system to measure textile density automatically and to improve fabrication efficiency. The proposed system uses cylindrical lens to optically scan the weftl information of the fabric as well as convex lens to enlarge the weft images. The proposed system improves textile quality and provides constant density value to the whole textile range in the high speed fabrication process. 직물의 밀도를 측정하는 작업은 직물 제직 공정에서 매우 중요한 사항이나 일반적으로 직물 제직 공장에서는 고속의 제직 라인에서 수작업에 의해 비효율적으로 행해지고 있다. 따라서 직물 제직 공정에서 직물의 포목 교정을 통해 고품질의 직물을 생산하기 위해서는 정확한 밀도 측정 과저잉 필수적인 사항이다. 본 논문에서는 고속의 제직 공정에서 광학적인 실린더 렌즈를 이용하여 직물의 위사 정보를 검출한 후 밀도 측정을 자동화함으로써 양질의 직물 생산과 직물 생산 효율을 극대화하고자 자동 밀도 측정 시스템을 제안하였다. 제안한 자동 밀도 측정 시스템은 고속의 직물 제직 공정에서 직물의 전체 영역에 걸쳐 일정한 밀도를 유지시켜 고품질의 직물 생산을 가능하게 하였다.

피부색 정보와 얼굴의 구조적 특징 분석을 통한 얼굴 영상 인식 시스템

이응주,Lee Eung- Joo 한국융합신호처리학회 2000 융합신호처리학회 논문지 (JISPS) Vol.1 No.1

In this paper, we propose the face image recognition algorithm using skin color information, face region features such as eye, nose, and mouse, etc., and geometrical features of chin line. In the proposed algorithm, we used the intensity as well as skin color information in the HSI color coordinate which is similar to human eye system. The experimental results of proposed method shows improved extraction quality of face and provides adaptive extraction methods for the races. And also, we used chin line information as well as geometrical features of face such as eye, nose, mouse information for the improvement of face recognition quality, Experimental results shows the more improved recognition as well as extraction quality than conventional methods.

영상처리 기법을 이용한 차량 분류 및 인식 알고리즘

이응주,손영선,김성진 동명정보대학교 2002 저널 정보공학기술 Vol.1 No.-

In this paper, we propose the vehicle type classification and recognition algorithm using intensity variation and wheel distance features. In the proposed algorithm, we first calculate wheel distance from the extracted wheel regions based upon the variation of vertical and horizontal intensity of input image. Next, we can classify the input vehicles into three types such as small, medium and large vehicles. And also, we suggest a new feature vectors of wheel distance to recognize the classified input vehicles. In the experimental results, it was found that the proposed method can improve the accuracy of type recognition efficiency as well as the real-time problem. The proposed method was effective in classification and recognition of input vehicles in the real environments.