• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.793-799
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• 2007

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm, because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection with subpixel edge detection in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.353-356
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• 2007

chamfer 정합(matching)은 많은 응용분야에서 사용되온 에지(edge) 기반 정합기법으로, 변환된 모델에지와 영상에지간의 거리를 최소화하는 과정이다. 이 거리는 보통 거리변환을 이용하여 픽셀분해능으로 계산된다. 본 논문에서는 서브픽셀(subpixel) 거리계산을 위해 거리계산시 보간법을 사용하여, 정확한 chamfer 정합을 구현한, 개선된 chamfer 정합 방법을 제안한다. 또한, 보다 정밀한 정합을 위해, 최소거리를 갖는 픽셀위치의 주변영역을 이용하여 최적의 위치를 추정하지 않고, 서브픽셀로 실제 거리계산을 통해 최소 거리를 찾기 위해 Powell 의 최적화기법을 이용하였다. 실험결과는 제안된 방법의 타당성을 보여주었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.103-119
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• 2010

In this paper, we propose a subpixel shift estimation method using phase correlation with a local region for the registration of noisy images. Phase correlation is commonly used to estimate the subpixel shift between images, which is derived from analyzing shifted and downsampled images. However, when the images are affected by additive white Gaussian noise and aliasing artifacts, the estimation error is increased. Thus, instead of using the whole image, the proposed method uses a specific local region that is less affect by noises. In addition, to improve the estimation accuracy, iterative phase correlation is applied between selected local regions rather than using a fitting function. the restricted range is determined by analyzing the maximum peak and the two adjacent values of the inverse Fourier transform of the normalized cross power spectrum. In the experiments, the proposed method shows higher accuracy in registering noisy images than the other methods. Thus, the edge-sharpness and clearness in the super-resolved image is also improved.

• Journal of Sensor Science and Technology
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• v.7 no.5
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• pp.334-341
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• 1998

In this paper, we present a new interpolation scheme for image enhancement using nonlinear operator. In general, interpolation techniques are based on linear operators which are essentially lowpass filters, hence, they tend to blur fine details in the original image. In our approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.2
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• pp.103-113
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• 1991

The accuracy of input coordinates of ground control points and check points affects great influences to the results of ground coordinate computation in using SPOT digital image data. The original SPOT images displayed on CRT are not usually adequate for identifying the object features and determining the point positioning. Hence, appropriate image processing techniques such as contrast enhancement, subpixel interpolation, edge enhancement, and spatial filtering are needed. In this study, the principles of digital image processing needed for accurate three dimensional positioning and spectral characteristic analysis are investigated. The algorithms for the actual applications are developed and programmed. And using the developed image processing software, some SPOT P-mode and XS-mode images are merged into the SPOT P＋XS, the high-resolution color composite image.