• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.799-802
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• 2017

We attempt to combines concepts of Morphological Operator(MO) and Convolutional Neural Networks(CNN) to improve image-to-image translation. To do this, we propose an operation that approximates morphological operations. Also we propose S-Convolution, an operation that extends the operation to use multiple filters like CNN. The experiment result shows that it can learn MO with big filter using multiple S-convolution layer of small filter. To validate effectiveness of the proposed layer in image-to-image translation we experiment with GAN with S-convolution applied. The result showed that GAN with S-convolution can achieve distinct result from that of GAN with CNN.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.791-794
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• 2002

본 연구는 영상분석에서 이진 영상의 잡음제거 및 에지 검출을 위한 연구로 임펄스 잡음이 존재하는 영상의 잡음 제거는 임펄스가 크거나 잡음 에너지가 상대적으로 작을 때는 기존의 메디언 필터를 이용하여 잡음을 제거하지만 임펄스 잡음과 같지 않는 잡음이 존재하는 경우에는 본 연구에서 제안한 형태학적인 연산을 적용하여 잡음을 제거하고, 에지를 검출하는 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.431-435
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• 2008

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판과 구 차량 번호판이 혼합되어 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 형태학적 특징 및 차 연산과 ART2 알고리즘을 이용한 차량 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 차량 번호판 영상에서 차 연산을 이용하여 에지를 추출한 후에 블록 이진화를 한다. 이진화 된 차량 영상에서 신 구 차량 번호판의 형태학적 특성을 8방향 윤곽선 추적 알고리즘에 적용하여 잡음 영역을 제거하고, 차량의 번호판 영역을 추출한다 추출된 번호판 영역에 대하여 평균 이진화와 최대 최소 이진화를 적용하여 번호판의 개별 영역에 대한 형태학적 특성을 고려하여 잡음을 제거하고, Labeling 알고리즘을 적용하여 개별 문자를 추출한 후에 결합한다. 이렇게 분류된 개별 문자 및 숫자 코드를 ART2 알고리즘에 적용하여 학습 및 인식을 한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 녹색 번호판과 흰색 번호판 이미지 각각 100장을 대상으로 실험한 결과, 제시 된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.253-260
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• 2012

Target detection is very difficult with complex clutters in IRST(Infrared Search and Track) system for a long distance target. Especially sea-clutter and ocean-surface with non-uniform temperature distribution make it difficult to detect incoming targets in images obtained in sea environment. In this paper, we propose a novel method based on morphological method for estimation of ocean surface with non-uniform temperature flow. In order to estimate the exact ocean surface temperature flow, we divided it into upper and lower bound flow. And after estimating it, the final ocean surface temperature flow is derived by a mean value of the estimated results. Also, we apply the multi-weighted technique with a variety of sizes of structure elements to overcome sub-sampling effect by using morphology method. Experimental results for ocean surface images acquired from many different environments are compared with results of existing method to verify the performance of the proposed methods.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.288-294
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• 2000

In this paper, an efficient detail extraction technique for a progressive coding scheme is proposed. The existing technique using the top-hat transformation yields an efficient extraction scheme for isolated and visually important details, but yields an inefficient results containing significant redundancy extracting the contour information. The proposed technique using the strong edge feature extraction property of the morphological Laplacian in this paper can reduce the redundancy, and thus provides lower bit-rate. Experimental results show that the proposed technique is more efficient than the existing one, and promise the applicability of the morphological Laplacian operator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2785-2791
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• 2015

In this paper, neddle detection algorithm for the removal of needle stuck into skin in oriental clinic is presented. First, in the proposed method, potential candidate areas of each needle are selected by using the morphological open operation in a gray image, and the false candidates are removed by considering their area size. Next, edge points are extracted using canny edge detector in selected candidate areas, line segments are approximated using the edge points. Based on the direction of line segment and the distance between two line segments, two main line segments of the needle are extracted. The final verification of needle is accomplished by using the morphological analysis of these two line segments. In the experiments, the detection rate of proposed method reaches to 97.5% for the 16 images containing 119 needles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2277-2282
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• 2009

In this paper, we proposed a new recognition method can be used in application systems using morphological features, difference operators and ART2 algorithm. At first, edges are extracted from an acquired car image by a camera using difference operators and the image of extracted edges is binarized by a block binarization method. In order to extract license plate area, noise areas are eliminated by applying morphological features of new and existing types of license plate to the 8-directional edge tracking algorithm in the binarized image. After the extraction of license plate area, mean binarization and mini-max binarization methods are applied to the extracted license plate area in order to eliminated noises by morphological features of individual elements in the license plate area, and then each character is extracted and combined by Labeling algorithm. The extracted and combined characters(letter and number symbols) are recognized after the learning by ART2 algorithm. In order to evaluate the extraction and recognition performances of the proposed method, 200 vehicle license plate images (100 for green type and 100 for white type) are used for experiment, and the experimental results show the proposed method is effective.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.41-50
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• 1999

In this paper, the new VLSI architecture of a reconstruction filter for morphological image segmentation is proposed. The filter, based on the $h_{max}$ operation, simplifies the interior of each region while preserving the boundary information. The proposed architecture adopts a partitioned memory structure and an efficient image scanning strategy to reduce the operations. The proposed memory partitioning scheme makes it possible that every data required for processing can be read from each memory at a time, resulting in parallel data processing. By the extended connectivity consideration, the operation is much decreased because more simplification is achieved in scanning stage. The selective raster scan strategy endows the satisfactory noise removal capability with negligible hardware complexity increase. The proposed architecture is designed using VHDL, and functional evaluation is performed by the CAD tool, Mentor. The experiment results show that the proposed architecture can simplify image profile with less than 18% operations of the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.525-532
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• 2000

본 논문은 영상에서 형태적 정보를 추출하는데 사용되는 수학적 형태학(mathematical morphology)에 퍼지 집합 이론을 적용하여 새로운 퍼지 수학적 형태학을 제안한다. 일반적인 수학적 형태학은 이진 영상에만 적용되는 한계를 가지고 있었다. 이를 그레이 스케일 영상에도 적용 가능하도록 한 Sinha와 Dougherty[8]이 제안한 방법도 기하학적 형태 변환을 보장하지 못하는 결점이 있었는데 본 논문에서는 그 결점을 제거하는 새로운 수축(erosion)과 확장(dilation) 연산을 정의하고 그 특성을 연구하였다. 본 논문이 제안한 방법과 [8]의 방법을 실제 영상에 대한 실험으로 비교하였다.

• The Journal of Korean Institute of Information Technology
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• v.15 no.12
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• pp.165-171
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• 2017

This paper proposes a method of support-generation using morphological image processing instead of geometric calculations. The geometric computational cost is dependent on the shape, but our method is independent on the shape. For obtaining the external support area for extrusion shape, we represents morphological operations between two sliced layer images and shows results of each operation stages. Internal support area is evaluated from erosion and opening operations with the sliced-layer image. In these support areas, the supporter image is generated using the designed support structures. Also, we made a DLP printer and the STL model included supporter-structure is printed by the DLP printer. We confirmed the necessity of support-generation method with the support structures individually dependent on materials by looking at the printed results.