• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.3
• /
• pp.591-597
• /
• 2012

Medical device performance has been advanced while images are expected to be acquired with further higher quality and pertinent applicability as images have been increasing in importance in analyzing major organs. Recent high frequency of image processing by MATLAB in image analysis area accounts for the intent of this study to segment pulmonary vessels by means of MATLAB. This study is to consist of 3 phases including pulmonary region segmentation, pulmonary vessel segmentation and three dimensional connectivity assessment, in which vessel was segmented, using threshold level, from the pulmonary region segmented, vessel thickness was measured as two dimensional refining process and three dimensional connectivity was assessed as three dimensional refining process. It is expected that MATLAB-based image processing should contribute to diversity and reliability of medical image processing and that the study results may lay a foundation for chest CT images-related researches.

• The KIPS Transactions:PartB
• /
• v.13B no.3 s.106
• /
• pp.215-222
• /
• 2006

People health improvement is becoming new subject through the combining with the oriental medicine diagnosis theory and IT technology. To do this, firstly, it needs sicked data that supply the visualization, objectification and quantification method. Especially, if an ocular inspection can be more objective and visual expression in oriental medicine, it seems to offer the biggest opportunity in diagnosis field. In this study, I propose a diagnosis to check the symptoms of heart diagnosis. Our research aim is on the visualization of diagnosis using image processing system which it can be actual analysis about the symptom of heart. To catch up this study, through the color support assistance by face image processing, I devide the face area and analyze the face form and also extract face characteristic point in heart disease diagnosis using oriental medicine based on an ocular inspection method. I would like to prove the usefulness of the method that proposed by an experiment.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2262-2270
• /
• 1999

In this paper, we describe gesture recognition algorithm using computer vision sensor and HMM. The automatic hand region extraction has been proposed for initializing the tracking of the tele-operation gestures. For this, distance informations(disparity map) as results of stereo matching of initial left and right images are employed to isolate the hand region from a scene. PDOE(positive difference of edges) feature images adapted here have been found to be robust against noise and background brightness. The KNU/KAERI(K/K) gesture instruction set is defined for tele-operation in atomic electric power stations. The composite recognition model constructed by concatenating three gesture instruction models including pre-orders, basic orders, and post-orders has been proposed and identified by discrete HMM. Our experimental results showed that consecutive orders composed of more than two ones are correctly recognized at the rate of above 97%.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.6
• /
• pp.712-716
• /
• 2010

In this paper, we propose a novel shape-based approach to detect CNV regions (CNVR) by analyzing the coverage graph obtained by aligning the giga-sequencing data onto the human reference sequence. The proposed algorithm proceeds in two steps: a filtering step and a post-processing step. In the filtering step, it takes several shape parameters as input and extracts candidate CNVRs having various depth and width. In the post-processing step, it revises the candidate regions to make up for errors potentially included in the reference sequence and giga-sequencing data, and filters out regions with high ratio of GC-contents, and returns the final result set from those candidate CNVRs. To verify the superiority of our approach, we performed extensive experiments using giga-sequencing data publicly opened by "1000 genome project" and verified the accuracy by comparing our results with those registered in DGV database. The result revealed that our approach successfully finds the CNVR having various shapes (gains or losses) in HLA (Human Leukocyte Antigen) region.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.18 no.3
• /
• pp.315-322
• /
• 2000

DSM(Digital Surface Model) is a digital model which represents the surface elevation of a region. DSM is necessary for orthoimage generation, and frequently used in man-made object extraction from aerial photographs nowadays. Image matching technique enables automatic DSM generation. This proposed a image matching method which can be applied to automatic generation of DSM for Built-up Area. The matching method proposed is to find conjugate points and conjugate lines from overlapping aerial images. In detecting conjugate points, the positional relation between possible conjugate point pair as well as correlation of pixel gray value is compared. In detecting conjugate lines, the color attribute of flank region of line, shape of line, positional relation between neighborhood points and lines, and the connection relation between lines are compared. The proposed matching method is assumed to be useful for DSM generation including Built-up Area.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7C
• /
• pp.554-564
• /
• 2012

The vehicle recognition consists of two steps; the vehicle region detection step and the vehicle identification step based on the feature extracted from the detected region. Features using linear transformations have the effect of dimension reduction as well as represent statistical characteristics, and show the robustness in translation and rotation of objects. Among the linear transformations, the NMF(Non-negative Matrix Factorization) is one of part-based representation. Therefore, we can extract NMF features with sparsity and improve the vehicle recognition rate by the representation of local features of a car as a basis vector. In this paper, we propose a feature extraction using NMF suitable for the vehicle recognition, and verify the recognition rate with it. Also, we compared the vehicle recognition rate for the occluded area using the SNMF(sparse NMF) which has basis vectors with constraint and LVQ2 neural network. We showed that the feature through the proposed NMF is robust in the urban scene where occlusions are frequently occur.

• Journal of Environmental Science International
• /
• v.13 no.12
• /
• pp.1109-1115
• /
• 2004

This study was investigated the residual contents of sulfur dioxide on the 373 kinds of herbal medicine distributed from Korea, China, and Japan. A modified Monier-Williams method was described for the determination of $SO_{2}$ contents in herbal medicines. The residual contents of $SO_{2}$ were not detected at 221 products$(59.8{\%})$ in total 373 products. Regardless of region, $SO_{2}$ contents were not found at Farfarae Flos, Zizyphi Spinosi Semen, Castanea crenata, and Strychni Ignatii Semen. But it's found at Asparagi Radix, Codonopsitis Radix, Lilii Bulbus, and Kaempferiae Rhizoma of every region collected the samples. Also, $SO_{2}$ contents were not detected at the herbal medicines which collected cultural fields of dometic. $SO_{2}$ contents ranged 11$\~$3990 mg/kg(mean 152 mg/kg) at domestic samples, 11$\~$3440 mg/kg(mean 603 mg/kg) at imported samples. After treated with water wash and hot water extraction, the reduction rates of sulfur dioxide were appeared with $24.4{\%}\~68.7{\%}\;and\;83.8{\%}\~100.0{\%},$ respectively. These data will be used to establish a criteron of residual sulfur dioxide in herbal medicines.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.1
• /
• pp.59-67
• /
• 2008

In this paper we propose an algorithm to extract the license plate regions from Korean car images. The idea of this paper is that we first find the four digits in the input car image and then segment the plate region using the digit information. Out method has advantage of segmenting simultaneously the plate regions and four digits regions. The first step finds and groups the connected components with proper sizes as candidate digits. The second step applies an serial alignment condition to find out probable 4-digits. In the third step, we recognize the candidate digits and assign the confidence values to each of them. The final step extracts the license plate region which has the highest confidence value. We used the Perfect Metrics classification algorithm to estimate the confidence. In our experiment, we got 97.23% and 95.45% correct detection rates, 0.09% and 0.11% false detection rates for 4,600 daytime and 264 nighttime images, respectively.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.2
• /
• pp.44-51
• /
• 2009

Text understand in natural images has become an active research field in the past few decades. In this paper, we present an automatic recognition system in Korean signboards with a complex background. The proposed algorithm includes detection, binarization and extraction of text for the recognition of shop names. First, we utilize an elaborate detection algorithm to detect possible text region based on edge histogram of vertical and horizontal direction. And detected text region is segmented by clustering method. Second, the text is divided into individual characters based on connected components whose center of mass lie below the center line, which are recognized by using a minimum distance classifier. A shape-based statistical feature is adopted, which is adequate for Korean character recognition. The system has been implemented in a mobile phone and is demonstrated to show acceptable performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.5
• /
• pp.610-616
• /
• 2012

In this paper, we present a method to detect an object such as ship, rock and buoy from sea IR image for the safety navigation. To this end, we do the image smoothing first and the apply watershed algorithm to segment image into subregions. Since watershed algorithm almost always produces over-segmented regions, it requires posterior merging process to get meaningful segmented regions. We propose an efficient merger algorithm that requires only two times of direct access to the pixels regardless of the number of regions. Also by analyzing IR image obtained from sea environments, we could find out that most horizontal edge come out from object regions. For the given input IR image we extract horizontal edge and eliminate isolated edges produced from background and noises by adopting morphological operator. Among the segmented regions, the regions that have horizontal edges are extracted as final results. Experimental results show the adequacy of the proposed method.