• Journal of the Optical Society of Korea
• /
• v.20 no.3
• /
• pp.381-388
• /
• 2016

The performance of a staring infrared imaging system can be characterized based on estimating the modulation transfer function (MTF). The slant edge method is a widely used MTF estimation method, which can effectively solve the aliasing problem caused by the discrete undersampling of the infrared focal plane array. However, the traditional slant edge method has some limitations such as the low precision of the edge angle extraction and using the approximate function to fit the edge spread function (ESF), which affects the accuracy of the MTF estimation. In this paper, we propose a modified slant edge method, including an edge angle extraction method that can improve the precision of the edge angle extraction and an ESF fitting algorithm which is based on the transfer function model of the imaging system, to enhance the accuracy of the MTF estimation. This modified slant edge method presents higher estimation accuracy and better immunity to noise and edge angle than other traditional methods, which is demonstrated by the simulation and application experiments operated in our study.

• Journal of information and communication convergence engineering
• /
• v.9 no.3
• /
• pp.276-281
• /
• 2011

This paper presents a method of constructing the switching function using edge-valued decision diagrams. The proposed method is as following. The edge-valued decision diagram is a new data structure type of decision diagram which is recently used in constructing the digital logic systems based on the graph theory. Next, we apply edge-valued decision diagram to function minimization of digital logic systems. The proposed method has the visible, schematic and regular properties.

• Journal of Power System Engineering
• /
• v.2 no.3
• /
• pp.60-67
• /
• 1998

Edge detection is the first step and very important step in image analysis. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that evaluates the quality of edge configurations. The cost function can be used as a basis for comparing the performances of different detectors. This cost function is made of desirable characteristics of edges such as thickness, continuity, length, region dissimilarity. And we use a simulated annealing algorithm for minimum of cost function. Simulated annealing are a class of adaptive search techniques that have been intensively studied in recent years. We present five strategies for generating candidate states. Experimental results(building image and test image) which verify the usefulness of our simulated annealing approach to edge detection are better than other operator.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.273-273
• /
• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• Current Optics and Photonics
• /
• v.2 no.1
• /
• pp.69-78
• /
• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.11 no.1
• /
• pp.73-84
• /
• 1986

A statistical method is proposed which estimates an edge that is one of the basic features in image understanding. The conventional edge detection techniques are performed well for a deterministic singnal, but are not satisfactory for a statistical signal. In this paper, we use the likelihood function which takes account of the statistical property of a signal, and derive the decision function from it. We propose the maximum likelihood edge detection technique which estimates an edge point which maximizes the decision function mentioned above. We apply this technique to statistecal signals which are generated by using the random number generator. Simnulations show that the statistical edge detection technique gives satisfactory results. This technique is extended to the two-dimensional image and edges are found with a good accuracy.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.6
• /
• pp.454-458
• /
• 2001

Based on a fuzzy system representation of gray scale images, we derive and edge detection algorithm whose convolution kernel is different from the known kernels such as those of Robert's Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3$\times$3 kernel. We also that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.197-200
• /
• 2007

Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.6
• /
• pp.1156-1161
• /
• 2007

Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.4
• /
• pp.38-45
• /
• 2003

This paper presents a meta-heuristic solution technique, Ant System (AS)algerian to solve edge detection problem. We define the quality of edge in terms of dissimilarity, continuity, thickness and length. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that inversely evaluates the quality of edge configuration. Twelve windows for enhancing dissimilarity regions based on the valid edge structures are used. The AS algorithm finds the optimal set of edge pixels based on the cost function. The experimental results show that the properly reduced set of edge pixels could be found regardless how complicated the image is.