• Journal of Korean Port Research
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• v.13 no.2
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• pp.303-312
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• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.9-16
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• 2012

The research of vehicle license plate recognition has been widely studied for the smart city project. The license plate recognition can be hard due to the geometric distortion and the image quality degradation in case of capturing the driving car image at CCTV without trigger signal on the road. In this paper, the high performance vehicle license plate recognition system using edge-based segment image is introduced which is robust in the geometric distortion and the image quality degradation according to non-trigger signal. The experimental results of the proposed real time license plate recognition algorithm which is implemented at the CCTV on the road show that the plate detection rate was 97.5% and the overall character recognition rate of the detected plates was 99.3% in a day average 1,535 vehicles for a week operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.874-877
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• 2012

This paper proposes the new method based on contour following method with directional angle to segment the cell into the nuclei. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. this paper, improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the Thyroid Gland cell image with difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a result of experiment using features proposed in this paper, get a better segmentation rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells. The methods described in this paper be used immediately for discrimination of neoplastic cells.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.514-520
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• 2004

There are many techniques for underwater source localization. These are the methods based on TDOA (Time Difference Of Arrival) estimation. beamforming techniques and high resolution techniques, etc. In this Paper we estimate the underwater source position using MCPSP (Modified Cross Power Spectrum Phase) function that is calculated on frequency domain using sensors of small number. However, the performances of the localizing method based on MCPSP function drops greatly in the case of CW (Continuous Wave) signal . In this Paper we proposed the TDOA estimation method for pulsed CW signal. In the Proposed method we composed of new segment including a edge of ping. This segment was computed by short-time energy detection. With theoretical representation the performances of the proposed method were analyzed under various environment.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.61-70
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• 2023

Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.99-111
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• 2009

The result of Image segmentation, an indispensable process in image processing, significantly affects the analysis of an image. Despite the significance of image segmentation, it produces some problems when the variation of pixel values is large, or the boundary between background and an object is not clear. Also, these problems occur frequently when many objects in an image are placed very close by. In this paper, when the shape of objects in an image is circular, we proposed an algorithm which segment an each object in an image using the geometric characteristic of circular shape. The proposed algorithm is composed of 4 steps. First is the boundary edge extraction of whole object. Second step is to find the candidate points for further segmentation using the boundary edge in the first step. Calculating the representative circles using the candidate points is the third step. Final step is to draw the line connecting the overlapped points produced by the several erosions and dilations of the representative circles. To verify the efficiency of the proposed algorithm, the algorithm is compared with the three well-known cell segmentation algorithms. Comparison is conducted by the number of segmented region and the correctness of the inner segment line. As the result, the proposed algorithm is better than the well-known algorithms in both the number of segmented region and the correctness of the inner segment line by 16.7% and 21.8%, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1315-1318
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• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.241-244
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• 2005

Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.164-169
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• 2008

This paper is using motion tracking by image segmentation to monitor intruders and to confirm based on mobile the relevant information. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmental foreground object to the edge detecting the location specified by the edge of the median estimate extracted by analyzing the motion of the intruders to monitor. When a motion is detected, the detected image is transmitted by using the W AP pull basis image transmission method on the mobile client data terminal.