• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37A no.9
• /
• pp.792-798
• /
• 2012

Network Quotient, an important figure in modern society, the intelligibility of speech as a conversation partner to maximize pulling up feeling of liking it as much as possible has become an important issue. The humidity of air in the intelligibility of speech have many influences. Therefore, in this paper, we carried out experiment to apply voice signal analysis techniques which to analyze influenced vocal cords in 30%, 50% and 80%, maintaining a constant humidity of the environment. With this in mind, we carried out experiments on intensity and pitch of voice signal on twenty male 20s in maintaining a constant humidity 30%, 50% and 80% of humidity. Finally, we carried out study to draw a significance through statistical analysis measuring characteristic parameter of vocal cord function to change of humidity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.4
• /
• pp.441-448
• /
• 2010

This paper estimates the tree height using Airborne LiDAR that is obtained for each season to analyze its influence based on a canopyclosure and data fusion. The tree height was estimated by extracting the First Return (RF) from the tree and the Last Return (LR) from the surface of earth to assume each tree via image segmentation and to obtain the height of each tree. Each data on tree height that is collected from seasonal data and the result of tree height acquired from the data fusion were compared. A tree height measuring device was used to measure on site and its accuracy was compared. Also, its applicability on the result of fused data that is obtained through the Airborne LiDAR is examined. As a result of the experiment, the result of image segmentation for an individual tree was closer to the result of site study for 1 meter interval when compared to the 0.5 meter interval of point cloud. In case of the tree height, the application of fused data enables a closer site measurement result than the application of data for each season.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.15 no.10 s.89
• /
• pp.983-995
• /
• 2004

This paper introduces a pre-compensation filter for compensating dispersive and resonant properties experienced along the usage of non-ideal wideband antennas in impulse communication systems. It has been well blown that the transmitted impulse signal becomes deformed because of dispersive and resonant characteristics. Accordingly, in spite of using ideal template signal at the correlator in coherent receiver, these impairments degrade overall performance attributed to low level of coherence. To overcome this problem this paper exploits a realization technique of pre-compensation filter purposely installed at transmitter whose stability is automatically guaranteed because it has an inversion form of minimum-phase ARMA (Auto-Regressive Moving Average) system. The performance of proposed scheme will be shown in results from computer simulations to verify its affirmative impact on impulse communication system with regarding several distinctively shaped antennas.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.23 no.8
• /
• pp.967-975
• /
• 2012

This paper presents a method to measure reflection coefficients of microwave devices or antennas based on time domain analysis with sampling oscilloscopes. The reflection coefficients were extracted by the Fourier transformation of echo pulses from devices with respect to the 20 GHz incident pulse signals. The three-error terms, which are commonly used for the correction of a microwave network, were determined using a 3.5 mm calibration kit. In addition, a modified error-correction model associated with a directional coupler for reflection coefficient measurements is introduced. The results were compared with those of measured with a commercial vector network analyzer.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2003.06a
• /
• pp.94-97
• /
• 2003

In this Paper, propose for MLP(multilayer perception) neural network that uses optimization recognition training scheme for the wavelet transform and the numeral image add to noise, and apply this system in Numeral Recognition. As important part of original image information preserves maximum using the wavelet transform, node number of neural network and the loaming convergence time did size of input vector so that decrease. Apply in training vector, examine about change of the recognition rate as optimization recognition training scheme raises noise of data gradually. We used original image and original image added 0, 10, 20, 30, 40, 50㏈ noise (or the increase of numeral recognition rate. In case of test image added 30∼50㏈, numeral recognition rate between the original image and image added noise for training Is a little But, in case of test image added 0∼20㏈ noise, the image added 0, 10, 20, 30, 40 , 50㏈ noise is used training. Then numeral recognition rate improved 9 percent.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.44-52
• /
• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.3
• /
• pp.198-204
• /
• 2004

This study suggests a sentence generating method to help those who have language impediment with their communication. The method suggested in this study was constructed into a system in order to be applied to AAC system. AAC system is a personal portable device that generates sentences. Those who have language impediment need another communication method, causes inconvenience when used in a conversation with those who don't have the same trouble. The method of inputting both consonants and vowels can be inconvenient and time consuming for a conversational communication because of the number of the key strokes. The lexical information for the sentence generating of this study defines the user's domain, collects the adequate words and sentences, and extracts and classifies the characteristics of the collected words. The comparison between the number of key strokes for sentence generating using the system and that of inputting consonants and vowels using a keyboard was made in order to evaluate the usefulness the sentence generating method.

• Journal of the Korean association of regional geographers
• /
• v.12 no.4
• /
• pp.496-507
• /
• 2006

A hybrid approach integrating both high-resolution and hyperspectral data sets was used to map vegetation cover of a coastal lowland area in the Hawaii Volcanoes National Park. Three common grass species (broomsedge, natal redtop, and pili) and other non-grass species, primarily shrubs, were focused in the study. A 3-step, hybrid approach, combining an unsupervised and a supervised classification schemes, was applied to the vegetation mapping. First, the IKONOS 1-m high-resolution data were classified to create a binary image (vegetated vs. non--vegetated) and converted to 20-meter resolution percent cover vegetation data to match AVIRIS data pixels. Second, the minimum noise fraction (MNF) transformation was used to extract a coherent dimensionality from the original AVIRIS data. Since the grasses and shubs were sparsely distributed and most image pixels were intermingled with lava surfaces, the reflectance component of lava was filtered out with a binary fractional cover analysis assuming that tile total reflectance of a pixel was a linear combination of the reflectance spectra of vegetation and the lava surface. Finally, a supervised approach was used to classify the plant species based on tile maximum likelihood algorithm.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.1
• /
• pp.8-14
• /
• 2005

The implementation of vision system using CCD camera which measures the earing rate of aluminium CAN is represented in this paper. In order to optimize the input image, the object of the input image is separated and the position of the image is calibrated. In the preprocessing, the definition of image is improved by the histogram equalization, and then the edges of the input image are detected by the Robert mask. The heights of the four ears and angles of the aluminium CAN are measured manually with the digital vernier calipers in industry. It takes 30 seconds to measure manually the height of one direction of the aluminium CAN at least three times. However, when the proposed system in this paper is applied, it takes 0.02 seconds only. In conclusion, the efficiency of the proposed system is higher than that of the system used in the industry.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.3
• /
• pp.34-40
• /
• 2003

The paper presents a method to detect dissolve shots of video scene change detections in an MPEG compressed domain. The proposed algorithm uses color-R DCT coefficients of Ⅰ, P-frames for a fast operation and accurate detection and a minimum decoding process in MPEG sequences. The paper presents a method to detect dissolve shot for three-dimensional visualization and analysis of Image in order to recognize easily in computer as a human detects accurately shots of scene change. First, Color-R DCT coefficients for 8*8 units are obtained and the features are summed in a row. Second, Four-step analysis are Performed for differences of the sum in the frame sequences. The experimental results showed that the algorithm has better detection performance, such as precision and recall rate, than the existing method using an average for all DC image by performing four step analysis. The algorithm has the advantage of speed, simplicity and accuracy. In addition. it requires less amount of storage.