Sang-il Park

A new directional filter bank for image analysis and classification

A new directional filter bank for image analysis and classification is proposed. This paper introduces an improved structure in order to visualize subband outputs of the directional filter banks, while retaining the attractive properties of the original directional filter banks such as 1-D separable filtering, perfect reconstruction, and maximal decimation. Using this structure, any arbitrary 2/sup n/ band directional filter bank can be implemented by cascading simple directional filter bank blocks, unlike the original structure that needs a parallel structure for visualizing subband outputs. Also, in order to have nondistorted phase information in the subbands for visualization, both FIR and IIR filter prototypes that can be implemented efficiently are provided for linear phase filtering. This paper shows the approach proposed here can be applied to image analysis and classification.

Directional filter bank-based fingerprint feature extraction and matching

The paper presents a new filter bank-based fingerprint feature extraction and matching method without needing to detect minutiae. The proposed method decomposes a fingerprint image into eight directional subband outputs using a directional filter bank (DFB) and then obtains directional energy distributions for each block from the decomposed subband outputs. Only dominant directional energy components are employed as elements of the input feature vector, which serves to reduce noise and improve efficiency. For the rotational alignment, additional input feature vectors in which various rotations are considered are extracted, and these input feature vectors are compared with the enrolled template feature vector. The proposed method significantly reduces the memory cost and processing time associated with verification, primarily because of the efficient DFB structure and the exploitation of directional specific information. Experimental results validate the effectiveness of the proposed method in extracting fingerprint features and achieving good performance.

Fingerprint enhancement based on the directional filter bank

Fingerprints have been used as a means to identify individuals uniquely for a very long time in various situations. In order to achieve robust performance of an automatic fingerprint identification/verification system, it is essential to be associated with a fingerprint enhancement algorithm in the minutiae extraction stage. We present a novel fingerprint enhancement system based on the directional filter bank. The directional filter bank is a maximally decimated filter bank with perfect reconstruction property that is able to decompose wedge-shape frequency components by using an 1-D filter prototype. By using the newly improved visualizable subbands in addition to the previous features of the directional filter bank, an efficient enhancement can be achieved in terms of both computation and memory saving.

Emergency Ampacities of Direct Buried Three Phase Underground Cable Systems

A thermal model is formulated for the determination of the emergency transient ampacities of a three phase, horizontally spaced underground cable system. The model is based on a finite difference heat transfer analysis and the principle of superposition which permits the summation of the temperature rise of individual heat sources to eventually provide for the temperature rise of a multiple cable system. The thermal model is transformed into a complex computer program that is capable of calculating the real time cable temperature for any change in conductor current.

Introduction of next-generation 3D AFM for advanced process control

To fulfil advanced process control requirements for 1X node production, the semiconductor industry must cope with multiple parallel metrology requirements such as resolution, precision and accuracy enhancement in all directions to answer to new 3D integrated circuit fabrication methods. At the 1D and 2D levels, CDSEM and Scatterometry techniques are the workhorse techniques for production and process control. However, for process control of 3D devices and high resolution patterning such as direct self-assembly lithography, reference metrology is necessary to maintain a global process control uncertainty that is sufficient for production standards. CD-SEM and Scatterometry have intrinsic limitations that limit their utility for these cases, and new characterization methods are needed. Among the industrial reference techniques currently available, TEM and CD-AFM are generally employed to address this issues but both of these techniques have their own limitations for 1X node production. Nevertheless, they are also very useful for engineers to calibrate production CD metrology techniques and for more accurate process window and process development definition at the R&D level. Thus, there is a critical need to develop new technologies that build upon these capabilities while overcoming the limitations.

New three-dimensional AFM for CD measurement and sidewall characterization

As the feature size in the lithography process continuously shrinks, accurate critical dimension (CD) measurement becomes more important. A new 3-dimensional (3D) metrology atomic force microscope (AFM) has been designed on a decoupled XY and Z scanner platform for CD and sidewall characterization. In this decoupled scanner configuration, the sample XY scanner moves the sample and is independent from the Z scanner which only moves the tip. The independent Z scanner allows the tip to be intentionally tilted to easily access the sidewall. This technique has been used to measure photoresist line patterns. The tilted scanner design allows CD measurement at the top, middle, and bottom of lines as well as roughness measurement along the sidewall. The method builds upon the standard AFM tip design resulting in a technique that a) maintains the same resolution as traditional AFM, b) can be used with sharpened tips for increased image resolution, and c) does not suffer from corner inaccessibility from large radius of curvature tips.

Automatic recognition of SAR targets using directional filter banks and higher-order neural networks

This paper presents a new approach for the classification of SAR targets that combines maximally decimated directional filter banks with higher-order neural networks (HONNs). HONNs are neural networks that permit the input signals to be multiplied together in addition to the more common operations such as weighting, summing, and pointwise nonlinearities of typical neural nets. HONNs have long been proposed as image classifiers whose performance can be made invariant to geometric transformations of the input imagery by using a method for decreasing dimensionality such as coarse coding. Most past image classifiers using HONNs have been tuned for carefully thresholded binary images, which generally cannot be derived from low-contrast imagery such as SAR without a significant loss of information. As an alternative, we use a novel HONN implementation that accepts gray-level input pixels using directional filter banks. In order to do this, a new modified tree-structured directional filter bank structure is proposed in this paper, where each of the subbands has directional visual information from a given input. The performance of the proposed approach is demonstrated with imagery taken from the public MSTAR database.

Multidimensional wavelets for target detection and recognition

The work described in this paper addresses the use of the four-dimensional continuous wavelet transform (CWT) for automatic target recognition (ATR) and detection. This transform is an overcomplete representation with four coordinates: two spatial, t1 and t2; a rotational coordinate, (theta) ; and a scale coordinate, a. Two central ideas are discussed in connection with the transforms application to target recognition. The first is cross-scale reconstruction, which refers to exploiting the dominate presence of target features across scales. The second is utilizing the non-spatial coordinate space as a working environment for feature extraction and classification. This aspect is unique to the multidimensional wavelet transform, emanating from the inherent redundancy in the transform representation. Some conclusions are drawn in the last section regarding the utility of the CWT for ATR, and the transforms potential as an analysis tool.

High-throughput automatic defect review for 300mm blank wafers with atomic force microscope

While feature size in lithography process continuously becomes smaller, defect sizes on blank wafers become more comparable to device sizes. Defects with nm-scale characteristic size could be misclassified by automated optical inspection (AOI) and require post-processing for proper classification. Atomic force microscope (AFM) is known to provide high lateral and the highest vertical resolution by mechanical probing among all techniques. However, its low throughput and tip life in addition to the laborious efforts for finding the defects have been the major limitations of this technique. In this paper we introduce automatic defect review (ADR) AFM as a post-inspection metrology tool for defect study and classification for 300 mm blank wafers and to overcome the limitations stated above. The ADR AFM provides high throughput, high resolution, and non-destructive means for obtaining 3D information for nm-scale defect review and classification.

Motion estimation using the spatio-temporal continuous wavelet transform: new results and alternative implementations

The spatio-temporal continuous wavelet transform (CWT) has proven useful for motion estimation (Me) applications. We present tracking results that highlight the ability of the CWT approach to handle non-linear motion and time-varying object signatures (as those produced by 3D motion projected in the image plane). In addition, we present two low-complexity approaches that emulate the behavior of the CWT velocity selective filters. The first approach is based on infinity impulse response (IIR) approximations of the temporal response of the CWT filters. The second technique is based on directional decompositions and results in a novel 3D decomposition, the directional filter bank.