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Hydrogen is an element of significant interest for semiconductor process; however it cannot be detected by many available elemental analysis techniques. Secondary ion mass spectrometry (SIMS) is one of the few techniques for the measurement of hydrogen amount and depth distribution. Among all kinds of SIMS tools, magnetic sector, quadrupole and time-of-flight, quadrupole SIMS instrument usually has...
This paper proposed a novel method to enhance mammogram images used in detecting early signs of breast cancer. The proposed method uses a three level pyramid decomposition scheme that applies the squeeze box filter (SBF) instead of low-pass filtering. A previously proposed non-linear local enhancement technique is applied to the difference images to contrast enhance the structural details of a mammogram...
Traditionally, human facial expressions are recognized using standard images. These methods of recognition require subjective expertise and high computational costs. This article presents a novel facial expression recognition method using edge maps generated from standard images that can significantly improve computational efficiency. The edge maps are generated from a novel Bi-dimensional Empirical...
In this paper, we focus on the problem of Unmanned Aircraft System (UAS) boundary detection, one of the most important intermediate steps to intelligent acquisition and processing, and proposed a wavelet transform optimization scheme for the purpose of improving traditional edge detect operators performance. The experimental evidence on Global Hawk unmanned system boundary extraction indicates the...
Traditionally, Linear Prediction is used to predict future values of a signal using past values. The goal is to minimize prediction errors. In this paper, we propose a novel method of utilizing prediction errors to extract edges of images. In this method, smooth prediction errors are minimized while steep changes (larger errors) are amplified. Therefore, when applied to image edge detection, edge...
This article presents an edge detection method using fast Bidimensional EMD and mathematical morphological methods. It is shown that the detection results are better than other comparable algorithms. The optimization of the presented algorithm extracts sufficient features for intended applications.
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