• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.261-264
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• 2019

There is the boundary following algorithm called by blob coloring or connected region labeling, which means that each pixel of the internal region can be filled with group label values by the raster scanning. This process represents to assigns the individual label value to each region. In this paper an improved equivalent table algorithm to be simpler and faster than the previous tangled complex labelling algorithm will be proposed when grouping different labels to the same region. 8 steps algorithms for grouping in the equivalent table will be presented and the yielding results will be shown.

• Current Optics and Photonics
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• v.3 no.3
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• pp.220-226
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• 2019

A novel speckle-shifting ghost imaging (SSGI) technique is proposed in this paper. This method can effectively extract the edge of an unknown object without achieving its clear ghost image beforehand. However, owing to the imaging mechanism of SSGI, the imaging result generally contains serious noise. To solve the problem, we further propose a simple and effective method to remove noise from the speckle-shifting ghost image with a connected-region labeling (CRL) algorithm. In this method, two ghost images of an object are first generated according to SSGI. A threshold and the CRL are then used to remove noise from the imaging results in turn. This method can retrieve a high-quality image of an object with fewer measurements. Numerical simulations are carried out to verify the feasibility and effectiveness.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.49-52
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• 2017

Ganglion cysts are benign soft tissues usually encountered in the wrist. In this paper, we propose a method to extract a ganglion cyst region from ultrasonography images by using image segmentation. The proposed method using the possibilistic c-means (PCM) clustering method is applicable to ganglion cyst extraction. The methods considered in this thesis are fuzzy stretching, median filter, PCM clustering, and connected component labeling. Fuzzy stretching performs well on ultrasonography images and improves the original image. Median filter reduces the speckle noise without decreasing the image sharpness. PCM clustering is used for categorizing pixels into the given cluster centers. Connected component labeling is used for labeling the objects in an image and extracting the cyst region. Further, PCM clustering is more robust in the case of noisy data, and the proposed method can extract a ganglion cyst area with an accuracy of 80% (16 out of 20 images).

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.625-635
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• 2005

In this paper, we propose a hybrid approach for segmenting the lungs efficiently and automatically in chest CT images. The proposed method consists of the following three steps. first, lungs and airways are extracted by two- and three-dimensional automatic seeded region growing and connected component labeling in low-resolution. Second, trachea and large airways are delineated from the lungs by two-dimensional morphological operations, and the left and right lungs are identified by connected component labeling in low-resolution. Third, smooth and accurate lung region borders are obtained by refinement based on image subtraction. In experiments, we evaluate our method in aspects of accuracy and efficiency using 10 chest CT images obtained from 5 patients. To evaluate the accuracy, we Present results comparing our automatic method to manually traced borders from radiologists. Experimental results show that proposed method which use connected component labeling in low-resolution reduce processing time by 31.4 seconds and maximum memory usage by 196.75 MB on average. Our method extracts lung surfaces efficiently and automatically without additional processing like hole-filling.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.95-107
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• 1994

A new efficient contour following algorithm for connected-component labeling processing is proposed. The basic idea of the algorithm is that the total number of downward chain codes is the same as one of upward chain codes along the closed contour. If the chain code direction is upward, then region start mark is assigned at the chain code departure pixel and if the chain code is downward, then region end mark is assigned at the chain code arrival pixel. The proposed algorithm extracts directly the contour information from only the current direction information of chain. This makes the algorithm simple and fast and requires less memory with comparison to the conventional algorithms.The proposed contour following algorithm can be applied to the various kind of image processing such as region filling, restoration and region feature extraction.

• International Journal of Contents
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• v.8 no.1
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.358-363
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• 2009

Text region detection from the natural scene images used in a variety of applications, many research are needed in this field. Recent research methods is to detect the text region using various algorithm which it is combination of edge based and connected component based. Therefore, this paper proposes an text region detection using edge and regional minima/maxima transformation algorithm from natural scene images, and then detect the connected components of edge and regional minima/maxima, labeling edge and regional minima/maxima connected components. Analysis the labeled regions and then detect a text candidate regions, each of detected text candidates combined and create a single text candidate image, Final text region validated by comparing the similarity and adjacency of individual characters, and then as the final text regions are detected. As the results of experiments, proposed algorithm improved the correctness of text regions detection using combined edge and regional minima/maxima connected components detection methods.

• Journal of Sensor Science and Technology
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• v.12 no.3
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• pp.128-138
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• 2003

In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.794-803
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• 2009

In this paper, we will present a container auto-landing system, the system use the stereo camera to measure the container depth information. And the container region can be detected by using its hough line feature. In the line feature detection algorithm, we will detect the parallel lines and perpendicular lines which compose the rectangle region. Among all the candidate regions, we can select the region with the same aspect-ratio to the container. The region will be the detected container region. After having the object on both left and right images, we can estimate the distance from camera to object and container dimension. Then all the detect dimension information and depth inform will be applied to reconstruct the virtual environment of crane which will be introduce in this paper. Through the simulation result, we can know that, the container detection rate achieve to 97% with simple background. And the estimation algorithm can get a more accuracy result with a far distance than the near distance.