• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.37 no.2
• /
• pp.33-40
• /
• 2000

In this study, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements that are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have the characteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of KIISE:Software and Applications
• /
• v.32 no.6
• /
• pp.523-531
• /
• 2005

Existing methods for color image segmentation using diffusion can't preserve contour information, or noises with high gradients become more salient as the number of times of the diffusion increases, resulting in over-segmentation when applied to watershed. This paper proposes a method for color image segmentation by applying morphological operations together with nonlinear diffusion For an input image, transformed into LUV color space, closing by reconstruction and nonlinear diffusion are applied to obtain a simplified image which preserves contour information with noises removed. With gradients computed from this simplified image, watershed algorithm is applied. Experiments show that color images are segmented very effectively without over-segmentation.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.9
• /
• pp.67-75
• /
• 1999

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements tat are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have chatacteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.6
• /
• pp.1095-1106
• /
• 1994

This paper presents a method for determining optimal grayscale function processing(FP) morphological filters under the least square (LMS) error criterion. The optimal erosion and dilation filters with a grayscale structuring element(GSE) are determined by minimizing the mean square error (MSE) between the desired signal and the filter output. It is shown that convergence of the erosion and dilation filters can be achieved by a proper choice of the step size parameter of the LMS algorithm. In an attempt to determine optimal closing and opening filters, a matrix representation of both opening and closing with a basis matrix is proposed. With this representation, opening and closing are accomplished by a local matrix operation rather than cascade operations. The LMS and back-propagation algorithm are utilzed for obtaining the optimal basis matrix for closing and opening. Some results of optimal morphological filters applied to 2-D images are presented.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.48 no.4
• /
• pp.469-478
• /
• 2012

To manage, sort, and grade fishery resources, it is necessary to measure their morphometric characteristics. This labor-intensive task involves performing repetitive operations on land and on a research vessel. To reduce the amount of labor required, a vision-based automatic measurement system (VAMS) for the measurement of morphometric characteristics of flatfish, such as total length (TL), body width (BW), and body height (BH), has been developed as part of a database management system for fishery resources management. This system can also measure the mass (M) of flatfish. In the present study, we describe a morphological image processing algorithm for the measurement of certain characteristics of flatfish. This algorithm, which involves preprocessing, edge pattern matching, and edge point detection, is effective in cases where the flatfish being measured has a deformed tail and is randomly oriented. The satisfactory performance of the proposed algorithm is also demonstrated by means of experiments involving the measurement of the BW, TL and BH of a flatfish when it is straightened (BW : 117mm, TL : 329mm, BH : 24.5mm), when its tail is deformed, and when it is randomly oriented.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.4
• /
• pp.251-259
• /
• 2015

In this paper, a ship detection method is proposed; this method uses edge-based segmentation and histogram of oriented gradient (HOG) with the ship size ratio. The proposed method can prevent a marine collision accident by detecting ships at close range. Furthermore, unlike radar, the method can detect ships that have small size and absorb radio waves because it involves the use of a vision-based system. This system performs three operations. First, the foreground is separated from the background and candidates are detected using Sobel edge detection and morphological operations in the edge-based segmentation part. Second, features are extracted by employing HOG descriptors with the ship size ratio from the detected candidate. Finally, a support vector machine (SVM) verifies whether the candidates are ships. The performance of these methods is demonstrated by comparing their results with the results of other segmentation methods using eight-fold cross validation for the experimental results.

• Journal of Korea Multimedia Society
• /
• v.20 no.12
• /
• pp.1890-1900
• /
• 2017

Tangram game consists of seven pieces of polygons such as triangle, square, and parallelogram. Typical methods of image processing for object recognition may suffer from the existence of side thickness and shadow of the puzzle pieces that are dependent on the pose of 3D-shaped puzzle pieces and the direction of light sources. In this paper, we propose an image processing method that recognizes simple convex polygon-shaped objects irrespective of thickness and pose of puzzle objects. Our key algorithm to remove the thick side of piece of puzzle objects is based on morphological operations followed by logical operations with edge image and background image. By using the proposed object recognition method, we are able to implement a stable tangram game applications designed for tablet computers with front camera. As the experimental results, recognition rate is about 86 percent and recognition time is about 1ms on average. It shows the proposed algorithm is fast and accurate to recognize tangram blocks.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.9
• /
• pp.1239-1247
• /
• 1993

Mathematical morphology based on the set theory has been applied to various areas in image processing. In this study, we propose a new pyramid structure for binary images based on the morphological operations. We use a specific class of structuring elements to shrink or expand images, and prove that the whole operations are separable to construct the pyramid. Through a simulation study, we show that the pyramid can be used as a progressive image coding.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.12
• /
• pp.4866-4888
• /
• 2020

One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.66.2-66.2
• /
• 2015

In today's age when telecommunications using satellite has become part of our daily lives, one has to be employ preventive measures to avert any possible danger, of which solar activity is the major cause. Coronal mass ejections (CMEs) heading towards the Earth can lead to disturbances in the Earth's magnetosphere, if their magnetic field is oriented southward. Monitoring of solar filaments in this case becomes very very crucial, as their eruption is associated with most of the CMEs. Monitoring of solar filaments in this case becomes very very crucial, as their eruption is associated with most of the CMEs. Also, filaments show activation up to a few hours prior to launch of a CME and thus can provide advance warning. In this study, we present an algorithm for the detection of solar filaments seen in the extreme ultraviolet (EUV) from Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Various morphological operations are employed to identify and extract the filaments. These filaments are then tracked in order to determine their size and location continuously.