• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.4
• /
• pp.522-527
• /
• 2010

In this paper, a new MBHF(Morphology-Based Homomorphic filter) is presented to enhance contrast in mammographic images. The MBH filtering is performed based on the morphological sub-bands, in which an image is morphologically decomposed. The filter is designed to have optimal gain and structuring element in each sub-band through differential evolution. Experimental results show that the proposed method improves the contrast in mammographic images such that an evaluation criterion, WPSNR(Weighted Peak Signal to Noise Ratio) which takes into account human visual system is increased compared with a wavelet-based Homomorphic filter.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.1
• /
• pp.29-36
• /
• 2004

Generally, wavelet coefficients can be classified into two categories: large coefficients with much signal information and small coefficients with little signal component. This statistical characteristic of wavelet coefficient is approximated to Gaussian mixture model and efficiently applied to noise reduction. In this paper, we propose an image denoising method using mixture modeling of wavelet coefficients. Binary mask value is generated by proper threshold which classifies wavelet coefficients into two categories. Information of binary mask value is used to remove image noise. We also develope an enhancement method of mask value using morphological filter, and apply it to image denoising for improvement of the proposed method. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.799-802
• /
• 2017

We attempt to combines concepts of Morphological Operator(MO) and Convolutional Neural Networks(CNN) to improve image-to-image translation. To do this, we propose an operation that approximates morphological operations. Also we propose S-Convolution, an operation that extends the operation to use multiple filters like CNN. The experiment result shows that it can learn MO with big filter using multiple S-convolution layer of small filter. To validate effectiveness of the proposed layer in image-to-image translation we experiment with GAN with S-convolution applied. The result showed that GAN with S-convolution can achieve distinct result from that of GAN with CNN.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.66 no.3
• /
• pp.1-14
• /
• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.4
• /
• pp.509-515
• /
• 2004

In this paper we present the linear combination of a fuzzy opening and closing filter with locally adaptive structuring elements that can preserve the geometrical features of an image. Based on the adaptation algorithm of linear combination of the fuzzy opening and closing filter, the optimal structuring element for image representation is obtained. The optimal structuring element is an indicator of the shape and direction of an object's image, which is useful in filtering, multi resolution, segmentation, and recognition of an image.

• Language and Information
• /
• v.6 no.2
• /
• pp.105-128
• /
• 2002

Morphologically annotated corpora are the basis for many tasks of computational linguistics. Most current approaches use statistically driven methods of morphological analysis, that provide just POS-tags. While this is sufficient for some applications, a rule-based full morphological analysis also yielding lemmatization and segmentation is needed for many others. This work thus aims at 〔1〕 introducing a rule-based Korean morphological analyzer called Kormoran based on the principle of linearity that prohibits any combination of left-to-right or right-to-left analysis or backtracking and then at 〔2〕 showing how it on be used as a POS-tagger by adopting an ordinary technique of preprocessing and also by filtering out irrelevant morpho-syntactic information in analyzed feature structures. It is shown that, besides providing a basis for subsequent syntactic or semantic processing, full morphological analyzers like Kormoran have the greater power of resolving ambiguities than simple POS-taggers. The focus of our present analysis is on Korean text.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.1
• /
• pp.166-174
• /
• 2013

QRS detection of ECG is the most popular and easy way to detect cardiac-disease. But it is difficult to analyze the ECG signal because of various noise types. The important problem in recording ECG signal is a baseline wandering, which is occurred by rhythm of respiration and muscle contraction attaching to an electrode. Particularly, in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, baseline wander removing method based on morphological filter for efficient QRS detection method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. The signal distortion ratio of the proposed method is compared with other filtering method. Also, R wave detection is evaluated by using MIT-BIH arrhythmia database. Experiment result show that proposed method removes baseline wanders effectively without significant morphological distortion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.393-396
• /
• 2010

In this paper the process of transmitting images signal restore to image corrupted by impulse noise proposed alpha-trimmed mean filter. the proposed filter first identifies the noise pixels using the morphological noise detector and then removes the detected impulse noise using the alpha-trimmed mean filter. these proposed filter can realize the accurate noise detection and it can remove impulse noise effectively while preserving edge region in the image very well. Through the simulation, we compared with the existing methods and capabilties.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.28 no.5
• /
• pp.373-381
• /
• 2017

DBS(Doppler Beam Sharpening) algorithm is a way to improve azimuth resolution performance in radar. Since DBS image includes the is information about the search area of radar, various clutter components exist besides the target to be detected. To detect and track the desired target in a DBS image, it must be able to identify a target and the clutter components. In this paper, we describe how to use image size and terrain information(DTED) to identify the target in a DBS image. By using morphological filter and chain code, it acquires image size and excludes the clutter components. By matching with DTED, we determine target.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.6
• /
• pp.909-914
• /
• 2002

In this thesis, noise reduction of image with impulse noise in circle image removed noise to harness existing median filter for noise reduction from image data of damage by noise when impulse noise is high or noise reduction is low, but it is not made up of noise reduction to harness existing median filter in case of existence of non-impulse noise. Therefore noise reduction of image with non-impulse noise had to remove noise by morphological arithmetic in this thesis's proposition. In contrast to median filtering, result of edge detection is more efficient after remove non-impulse noise by method of thesis's proposition and it compare and demonstrate through this experimentation.