• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.338-340
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• 2012

In images, the edge is an important element to analyze characteristics of the image and has been used selectively at several applications. Even now, many researches to detect and take advantage of theses edges are underway and in initially to detect edges, methods using the relation of adjacent pixels are proposed. Characteristic of these methods is that the processing speed of the algorithms is fast, but the specific weighted values are applied to all the pixels regardless of the images equally. In recent years, the research of the edge detection algorithm to adapt according to the image has been actively underway, in order to complement the drawbacks of the existing methods. Therefore, in order to detect the edge excellent characteristics In this paper, we proposed algorithm using adaptive mask.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.138-147
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• 1997

The ultrasonic images are corrupted by the granular pattern noise - a speckle noise. The speckle exist in the type of coherent imaging systems, and the speckle is the signal independent and multiplicative noise. In this paepr, we derive two filters using the gradient and symmetry. One is a noise suppression filter which removes noise while preserves the edges. It is named the ASRF-GS (Adaptive Speckle Removal Filer - Gradient and Symmetry). And the other is a edge detection filter which obtains the thin edge map, called the EDUGS(Edge Detection Using Gradient and Symmetry). The performance of the proposed noise suppression filter is evaluated by the IMPV(SNR improvement) and the Speckle Index(SI), and the perforamnce of the edge detection is evaluated by the edge detection error rate. According to the evaluated method, The SI reduced about 0.035, The IMPV improved about 1.265(dB), and the edge detection error rate is about 17.5%.

• Convergence Security Journal
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• v.8 no.4
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• pp.127-134
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• 2008

In this paper, we try to improve the accuracy of automatic measurement for analysis equipment by detecting efficiently the edge of a waterdrop with transparency. In order to detect the edge of a waterdrop with transparency, we use an edge detecting technique, MADD (Modified Adaptive Directional Derivative), which can identify the ramp edges with various widths as the perfectly sharp edges and respond effectively regardless of enlarging or reducing the image. The proposed edge detecting technique by means of perfect sharpening of ramp edges employs the modified adaptive directional derivatives instead of the usual local differential operators in order to detect the edges of image. The modified adaptive directional derivatives are defined by introducing the perfect sharpening map into the adaptive directional derivatives. Finally we apply the proposed method to contact angle arithmetic and show the effiency and validity of the proposed method.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.569-571
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• 1998

In this paper, we propose a method of restoring blurred images by an edge-sensitive adaptive filter. The direction of the edge is estimated using the properties of 2-D block FFT. Reduction of blurring due to the added noise during image transfer and the focus of lens caused by shooting a fast moving object is very important. To remove this phenomenon effectively, we can use the edge information obtained by processing the blurred images. The proposed algorithm estimates both the existence and the direction of the edge. On the basis of the acquired edge direction information, we choose the appropriate edge-sensitive adaptive filter, which enables us to get better images than images obtained by methods not considering the direction of the edge. The performance of the proposed algorithm is shown in the simulation result.

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

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.1
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• pp.37-55
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• 2023

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1610-1620
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• 2010

This paper proposes a motion-adaptive 3-D deinterlacing algorithm based on an adaptive-thresholded motion detection and an interpolation method using binary patterns to compensate motion missing and false motion errors. For efficient motion detection, we adaptively decided a threshold value according to the complexity of image. Many edge-based interpolation algorithms have been proposed to improve the subjective quality. Recently, to efficiently interpolate low angle edge and line, a method using predefined binary patterns has been proposed. In this paper, we propose an improved method by modifying the binary patterns. Simulation results have shown that the proposed method provides better performance than the existing methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.207-210
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• 2009

Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

• ETRI Journal
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• v.29 no.1
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• pp.59-69
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• 2007

We designed and fabricated a vision chip for edge detection with a $160{\times}120$ pixel array by using 0.35 ${\mu}m$ standard complementary metal-oxide-semiconductor (CMOS) technology. The designed vision chip is based on a retinal structure with a resistive network to improve the speed of operation. To improve the quality of final edge images, we applied a saturating resistive circuit to the resistive network. The light-adaptation mechanism of the edge detection circuit was quantitatively analyzed using a simple model of the saturating resistive element. To verify improvement, we compared the simulation results of the proposed circuit to the results of previous circuits.