• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.1
• /
• pp.33.3-33.3
• /
• 2019

Automatic, yet reliable methods to find and classify barred galaxies are going to be more important in the era of large galaxy surveys. Here, we introduce a new approach to classify barred galaxies by analyzing the butterfly pattern that Buta & Block (2001) reported as a bar signature on the potential map. We make it easy to find the pattern by moving the ratio map from a Cartesian coordinate to a polar coordinate. Our volume-limited sample consists of 1698 spiral galaxies brighter than Mr = -15.2 with z < 0.01 from the Sloan Digital Sky Survey/DR7 visually classified by Ann et al. (2015). We compared the results of the classification obtained by four different methods: visual inspection, ellipse fitting, Fourier analysis, and our new method. We obtain, for the same sample, different bar fractions of 63%, 48%, 36%, and 56% by visual inspection, ellipse fitting, Fourier analysis, and our new approach, respectively. Although automatic classifications detect visually determined, strongly barred galaxies with the concordance of 74% to 86%, automatically selected barred galaxies contain different amount of weak bars. We find a different dependence of bar fraction on the Hubble type for strong and weak bars: SBs are preponderant in early-type spirals, whereas SABs are in late-type spirals. Moreover, the ellipse fitting method often misses strongly barred galaxies in the bulge-dominated galaxies. These explain why previous works showed the contradictory dependence of the bar fraction on the host galaxy properties. Our new method has the highest agreement with visual inspection in terms of the individual classification and the overall bar fraction. In addition, we find another signature on the ratio map to classify barred galaxies into new two classes that are probably related to the age of the bar.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.327-336
• /
• 2004

For visual inspection system in real industrial environment, it is one of most important tasks to design fast and stable pattern matching algorithm. This paper presents an edge-based point correlation algorithm avoiding full search in visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties for applying to automated inspection system in factory environment. First of all, NGC algorithms need high time complexity and thus high performance hardware to satisfy real-time process. In addition, lighting condition in realistic factory environments if not stable and therefore intensity variation from uncontrolled lights gives many roubles for applying directly NGC as pattern matching algorithm in this paper, we propose an algorithm to solve these problems from using thinned and binarized edge data and skipping full point search with edge-map analysis. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the time complexity. Matching edges instead of using original gray-level pixel data overcomes NGC problems and pyramid of edges also provides fast and stable processing. All proposed methods are preyed from experiments using real images.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.5
• /
• pp.746-754
• /
• 2008

This paper proposes a method to detect calibration patterns for accurate camera calibration under complicated backgrounds and uneven lighting conditions of industrial fields. Required to measure object dimensions, the preprocessing of camera calibration must be able to extract calibration points from a calibration pattern. However, industrial fields for visual inspection rarely provide the proper lighting conditions for camera calibration of a measurement system. In this paper, a probabilistic criterion is proposed to detect a local set of calibration points, which would guide the extraction of other calibration points in a cluttered background under irregular lighting conditions. If only a local part of the calibration pattern can be seen, input data can be extracted for camera calibration. In an experiment using real images, we verified that the method can be applied to camera calibration for poor quality images obtained under uneven illumination and cluttered background.

• The Journal of the Korea Contents Association
• /
• v.7 no.1
• /
• pp.65-72
• /
• 2007

In this study, we used nondestructive test based on ultrasonic test as inspection method and compared backpropagation neural network(BPNN) with probabilistic neural network(PNN) as pattern recognition algorithm of weld flaws. For this purpose, variables are applied the same to two algorithms. Where, feature variables are zooming flaw signals of reflected whole signals from weld flaws in time domain. Through this process, we compared advantages/ disadvantages of two algorithms and confirmed application methods of two algorithms.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.99.2-99
• /
• 2002

Contents 1 In this paper a machine vision system for recognizing and classifying the patterns and marks engraved by die molding or laser marking on glass panel of computer monitor is suggested and evaluated experimentally. The vision system is equipped with a neural network based pattern classifier and searching process based on normalized grayscale correlation and adaptive binarization, which is applicable to the cases in which the segmentation of the pattern area from background using the ordinary blob coloring technique is quite difficult. Inspection process is accomplished via the way of NGC hypothesis and ANN verification. The proposed pattern recognition system is composed of three...

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.3
• /
• pp.39-44
• /
• 2006

In this study, we nodestructive test based on ultrasonic test as inspection method and compared backpropagation neural network(BPNN) with probabilistic neural network(PNN) as pattern recognition algorithm of welding flasw. For this purpose, variables are applied the same to two algorithms. Where, feature variables are zooming flaw signals of reflected whole signals from welding flaws in time domain. Through this process, we confirmed advantages/disadvantages of two algorithms and identified application methods of two algorithms.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.112-119
• /
• 2000

A die-casting junction method is usually used to manufacture the tub of an IH(induction heating) jar. If there is a very small air bubble in the junction area, the thermal conductivity is deteriorated and local overheat occurs. Such problem brings serious inferiority of the IH jar. In this paper, we propose a new method to detect such defect with simply measured thermal data. Thermal distribution of preheated tubs is obtained by scanning with infrared thermal sensors and analyzed with the statistic pattern recognition method. By defining the characteristic feature as the temperature difference between sensors and using ellipsoid function as decision boundary, a supervised learning method of genetic algorithm is proposed to obtain the required parpameters. After applying the proposed method to experiment, we have proved that the rate of recognition is high even for a small number of data set.

• Proceedings of the KSR Conference
• /
• 2006.11b
• /
• pp.719-722
• /
• 2006

At present, In korea one of big characteristics in electricity power market is unique seller but in the near future competitions are expected in the market. Another big trend is development of IT technology. Through IT, remote inspection for power usage are possible. So huge power consumer like KORAIL it is necessary to investigate power consumption pattern. This paper presents load consumption pattern for representative substation and billing system database program. Base on the substation annual power usage data, the characteristic of the substation power consumption are investigated and effective electrical billing system are compared each other. The database program was properly designed to examine the billings.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.1
• /
• pp.1-11
• /
• 1997

Austomated visual inspection(AVI) capability has become an important key component in the automated manufacturing system. In such a visual inspection system an intensity(or color) image of a scene is quickly affected by optical property of objects, condition and roughness of surface, lens and filters, image sensor property and lighting system. In particular, the lighting system disign is the most important factor, since it affects overall performance of the visual system. For fast and cheap automated visual inspection system it is important to obtain the good image quality which results from careful attention to the design of the lighting system. In this paper, the lighting subsystem of AVI system is analysed for the inspection of printed circuit board(PCB) patterns. The spectral reflectance of materials, which are composed of PCB, is measured for choosing the light source. The reflection property is theoretically obtained by a reflection model and also obtained by experiments which measure intensity with varying the viewing direction of image sensor and the lighting direction of illuminator. The illumination uniformity of a ring-type illuminator. The lighting system is designed based upon the experimental results and theoretial analysis.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.31 no.4
• /
• pp.367-373
• /
• 2011

Guided waves inspection techniques that are different with inspection technique by bulk waves are widely used in pipe line evaluation due to advantages of long distance inspection. However, most of pipe lines at industrial fields are buried and/or coated. In this case, due to the attenuation effect from soil and/or coating material, there are a lot of difficulty on inspection by conventional ultrasonic technique. In this paper, guided waves propagating patterns are calculated with respect to excitation mode by Normal Mode Expansion(NME). Guided waves patterns based on excited by single transducer and guided wave focusing technique have employed to analyze focusing pattern on a pipe. A longitudinal mode and high order flexural modes are used with various number of transducers to determine sensitivity. Guided waves energy excited by multi transducer with focusing algorithm was successfully focused at a desired point.