• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.75-80
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• 2016

The process of extracting external boundary of an object is a very important process for recognizing an object in the image. The proposed extraction method consists of two processes: External Boundary Extraction and Thinning. In the first step, external boundary extraction process separates the region representing the object in the input image. Then, only the pixels adjacent to the background are selected among the pixels constituting the object to construct an outline of the object. The second step, thinning process, simplifies the outline of an object by eliminating unnecessary pixels by examining positions and interconnection relations between the pixels constituting the outline of the object obtained in the previous extraction process. As a result, the simplified external boundary of object results in a higher recognition rate in the next step, the object recognition process.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.715-721
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• 2000

In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.34-39
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• 1999

In this paper, boundary extraction algorithm is suggested by removing boundary noises efficiently and simplifying object shape in binary image. To remove boundary noises, $2{times}2$ mask boundary extraction algorithm is modified . Proposed method is designed to generate a symmetric path for the parasitic branch noise and to analysis traced features on end point of noise. It can extract more simplified object boundary but preserve original object shape by combining white background color extraction result with foreground extraction result. The usefulness of the proposed method was proved through experiments with various binary images.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.181-183
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• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.123-129
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• 2006

High-resolution aerial color image offers great possibilities for geometric and semantic information for spatial data generation. However, shadow casts by buildings and trees in high-density urban areas obscure much of the information in the image giving rise to potentially inaccurate classification and inexact feature extraction. Though many researches have been implemented for solving shadow casts, few studies have been carried out about the extraction of features hindered by shadows from aerial color images in urban areas. This paper presents a asphalt road boundary extraction technique that combines information from aerial color image and LIDAR (LIght Detection And Ranging) data. The following steps have been performed to remove shadow effects and to extract road boundary from the image. First, the shadow regions of the aerial color image are precisely located using LEAR DSM (Digital Surface Model) and solar positions. Second, shadow regions assumed as road are corrected by shadow path reconstruction algorithms. After that, asphalt road boundary extraction is implemented by segmentation and edge detection. Finally, asphalt road boundary lines are extracted as vector data by vectorization technique. The experimental results showed that this approach was effective and great potential advantages.

• ETRI Journal
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• v.33 no.4
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• pp.547-557
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• 2011

This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.

• KSCI Review
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• v.15 no.1
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• pp.185-190
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• 2007

An image retrieval system is a piece of software that searches identical or similar images based on various image-specific features. This paper proposes a trademark image retrieval system that uses image colors and forms. In the proposed system, input images are segmented into several other regions, and color distribution histograms for different regions are extracted for use as color information. The proposed system uses form information through the preprocessing process such as boundary surface extraction, centroid extraction, angular sampling and, and through calculating the sums of the distances between the centroid and the boundary surfaces, standard deviations, and the ratios between long and short axes. Like this, the color and form information extracted is used to perform retrieval through measuring similarity.

• ETRI Journal
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• v.37 no.5
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• pp.1023-1031
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• 2015

In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.259-267
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• 2023

At a time when the demand for drones is increasing, a plan to utilize drone images was sought for efficient promotion of cadastral resurvey. To achieve the purpose of this study, the technical and legal status of drone images was reviewed, and through this, the possibility of using it for cadastral resurvey was primarily reviewed. subsequently, an experiment was conducted targeting the project district to examine whether drone images were applied to boundary extraction, which is the primary process of cadastral resurvey. As a result of the experiment, it was found that boundary extraction from images is possible. However, in some cases, it is impossible due to field conditions or image quality. Therefore, it is necessary first to apply cases where boundary extraction is possible to cadastral resurvey and seek solutions for some impossible cases. In particular, the image quality problem may have problems with the current technology, but it will also have problems with the existing drone equipment. So, standard for drone calibration should also be established. Finally, the cadastral resurvey surveying procedure using drones was also presented

• Journal of Ocean Engineering and Technology
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• v.25 no.1
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• pp.8-13
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• 2011

A compact array system of small buoys is used for wave energy extraction. To evaluate the performance of this system, hydrodynamic analysis is carried out in regular waves using the higher order boundary element method. The motion response of each buoy is calculated considering hydrodynamic interactions caused by other buoys. The effect of energy extraction device is modeled as a linear damping load. The efficiencies of energy conversion are compared using the various sizes and arrangements of the array system and the damping coefficients for energy extraction. The increase in size or the packing ratio of the system gives better efficiency. However, the wave condition and the cost for the system should be considered to optimize performance from the perspective of engineering and economics. The proposed nondimensionalized damping coefficient for energy extraction is 0.1~0.5.