• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1699-1704
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• 2009

If detected early enough, cervical cantor may have a good survival rate due to its preneoplastic state. However, the process is so time consuming that a medical expert can handle only a small amount of such examinations. In this paper, we propose a new nucleus extraction algorithm for uterine cervical pap smears in order to mitigate such burdens of medical experts. In the preneoplastic state cytodiagnosis images, it is important to differentiate three main areas - background, cytoplasm and nucleus. Thus, we apply lighting compensation and $3{\times}3$ mask of B channel in order to restore damaged image and remove noises respectively. The cell object is obtained from those clean binarized images with Grossfire algorithm. When there are clusters of cells, the target nucleus can be obtained with repetitive binarization of R channel brightness. In our experiment of using uterine cervical pap smears of 400 magnifications that is common in the diagnostic cytology, our method is able to extract 40 nucleus out of 45 population successfully.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1588-1593
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• 2005

In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.41-46
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• 2014

As the radioactive-related incidents have been occurred frequently such as Fukushima nuclear exposure incident, it is always considered radioactivity normal levels in radiation exposure as a most risk components at several government agencies. In this paper, the data were analyzed by information in the data beyond range of the attributes. The clustering analysis method is used by EM and SimpleKMeans algorithm. The experimental results about US Radioactive associated data is depending on the method of data analysis. It can be seen that the method of the algorithm is different depending on local value of the normal range. The governments need to pay attention to increase the investigation frequency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2121-2128
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• 2012

This paper proposed the real time face area detection using Wavelet transform and the strong detection algorithm that satisfies the efficiency of computation and detection performance at the same time was proposed. The detected face image recognizes the face by configuring the low-dimensional face symbol through the principal component analysis. The proposed method is well suited for real-time system construction because it doesn't require a lot of computation compared to the existing geometric feature-based method or appearance-based method and it can maintain high recognition rate using the minimum amount of information. In addition, in order to reduce the wrong recognition or recognition error occurred during face recognition, the input symbol of Hidden Markov Model is used by configuring the feature values projected to the unique space as a certain symbol through clustering algorithm. By doing so, any input face will be recognized as a face model that has the highest probability. As a result of experiment, when comparing the existing method Euclidean and Mahananobis, the proposed method showed superior recognition performance in incorrect matching or matching error.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.111-116
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• 2018

This paper compare the adaptive equalization performance of RMMA (Region-based MMA) and SCA (Square Contour Algorithm) in order to minimize the intersymbol interference that is occurred in communication channel when transmit the multilevel QAM signal. The RMMA used for improving the performance by translate to 4-level constant modulus and stability in current MMA algorithm, and the SCA used for the improving the performacne by combines the current CMA and RCA algorithm. These algorithms are aimed to improving the equalization peformance by applying the differenct principle each other in multilevel QAM signal, its different performance were compared by computer simulation in the same channel environment. For this, the output signal constellation of equalizer, residual isi, maximum distortion were applied in performance index. As a result, RMMA have more fairly good in every performance index such as signal point clustering capabilities and convergence speed compared to SCA. It is confired that the equalization noise due to misadjumstment was reduced in RMMA than SCA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.157-163
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• 2013

In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.67-75
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• 2013

Korea has developed coastal farming industry due to the environmental characteristics that its three sides are surrounded by sea. The damage of coastal farming industry caused by Asterias Amurensis with very strong reproductive rate and predaciousness has increased sharply every year. Moreover, Asterias Amurensis preys on living fish and shellfish and so the damage of fishermen is vern greater. In this paper, a method is proposed to extract effectively the features from the image of Asterias Amurensis acquired in the water. Because the proposed method extracts convex features using 6-directional scanning, it selects a fewer number of feature candidates than the conventional one. In addition, after selecting candidate concave points using the extracted convex features and centers of region, the final concave features are extracted. Due to the features of the starfish which lives in groups, individuals of the starfish in the input image are concentrated. Thus, it is significant to minimize the number of feature candidates extracted from the input image. The experimental results indicate an improvement of the proposed feature extraction method over the conventional one as evidenced by the fact that the feature extract was 88 % of the feature candidates.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.243-248
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• 2014

This study presents an investigation into the ways to detect the areas of object movement with Kinect's Depth Frame, which is capable of receiving 3D information regardless of external light sources. Applied to remove noises along the boundaries of objects among the depth information received from sensors were the blurring technique for the x and y coordinates of pixels and the frequency filter for the z coordinate. In addition, a clustering filter was applied according to the changing amounts of adjacent pixels to extract the areas of moving objects. It was also designed to detect fast movements above the standard according to filter settings, being applicable to mobile robots. Detected movements can be applied to security systems when being delivered to distant places via a network and can also be expanded to large-scale data through concerned information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1096-1101
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• 2005

An efficient method of estimating the spatial gaps between the connected components has been prposed to separatethe individual words from a handwritten legal amount on bank check. Owing to the inherent problem of underestimation or overestimation, the previous gap measures have much difficulty in being applied to the legal amounts that usually include the great shape variability by writer's unconstrained writing style and touching or irregular gaps between words by space limitation. In order to alleviate such burden and improve word separation performance, we have developed a modified version of each distance measure. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over $2-3\%$ of the word separation rate than their corresponding original distance measures.