This paper proposes a method for reconstructing accurate 3D surface points. To this end, robust and dense reconstruction with Shape-from-Silhouettes (SfS) and accurate multiview stereo are integrated. Unlike gradual shape shrinking and/or bruteforce large space search by existing space carving approaches, our method obtains 3D points by SfS and stereo independently, and then selects correct ones from them. The point selection is achieved in accordance with spatial consistency and smoothness of 3D point coordinates and normals. The globally optimized points are selected by graph-cuts. Experimental results with several subjects containing complex shapes demonstrate that our method outperforms existing approaches and our previous method.

A CMOS current-mode S-shape correction circuit with shape-adjustable control is proposed for suiting different LCD panel's characteristics from different manufactures. The correction shape is divided into three segments for easy curve-fitting using three lower order polynomials. Each segment could be realized by a corresponding current-mode circuit. The proposed circuit consists of several control points which are designed for tuning the correction shape. The S-shape correction circuit was fabricated using the 0.35 µm TSMC CMOS technology. The measured input dynamic range of the circuit is from 0 µA to 220 µA. The -3 dB bandwidth of the circuit is up to 262 MHz in a high input current region.

A can swells due to gas produced from an inner food caused by poor hermetic sealing of the can. This paper presents a measurement for the bottom shape to detect a swelled can by using the millimeter-wave imaging. For get higher spatial resolution and an adjustable focal distance, two collimated beam lenses were applied to the measurement system. First, a configuration of the system was studied with the electrical field intensity and focal distance by using full wave electromagnetic simulation. Next, the bottom shapes of cans with different pressure were evaluated quantitatively using the system. A shape change of 0.5 mm was detected with pressure difference of 50 kPa, and it is reasonable considering actual dimension of the can shape. A potential of the proposed detection method was presented.

This paper proposes a method for reconstructing a smooth and accurate 3D surface. Recent machine vision techniques can reconstruct accurate 3D points and normals of an object. The reconstructed point cloud is used for generating its 3D surface by surface reconstruction. The more accurate the point cloud, the more correct the surface becomes. For improving the surface, how to integrate the advantages of existing techniques for point reconstruction is proposed. Specifically, robust and dense reconstruction with Shape-from-Silhouettes (SfS) and accurate stereo reconstruction are integrated. Unlike gradual shape shrinking by space carving, our method obtains 3D points by SfS and stereo independently and accepts the correct points reconstructed. Experimental results show the improvement by our method.

This paper proposes a method for recognizing hand-shapes by using multi-viewpoint image sets. The recognition of a hand-shape is a difficult problem, as appearance of the hand changes largely depending on viewpoint, illumination conditions and individual characteristics. To overcome this problem, we apply the Kernel Orthogonal Mutual Subspace Method (KOMSM) to shift-invariance features obtained from multi-viewpoint images of a hand. When applying KOMSM to hand recognition with a lot of learning images from each class, it is necessary to consider how to run the KOMSM with heavy computational cost due to the kernel trick technique. We propose a new method that can drastically reduce the computational cost of KOMSM by adopting centroids and the number of images belonging to the centroids, which are obtained by using k-means clustering. The validity of the proposed method is demonstrated through evaluation experiments using multi-viewpoint image sets of 30 classes of hand-shapes.

A two-dimensional shape is generally represented with line drawings or object contours in a digital image. Shapes can be divided into two types, namely ordered and unordered shapes. An ordered shape is an ordered set of points, while an unordered shape is an unordered set. As a result, each type typically uses different attributes to define the local descriptors involved in representing the local distributions of points sampled from the shape. Throughout this paper, we focus on unordered shapes. Since most local descriptors of unordered shapes are not scale-invariant, we usually make the shapes in an image data set the same size through scale normalization, before applying shape matching procedures. Shapes obtained through scale normalization are suitable for such descriptors if the original whole shapes are similar. However, they are not suitable if parts of each original shape are drawn using different scales. Thus, in this paper, we present a scale-invariant descriptor constructed by von Mises distributions to deal with such shapes. Since this descriptor has the merits of being both scale-invariant and a probability distribution, it does not require scale normalization and can employ an arbitrary measure of probability distributions in matching shape points. In experiments on shape matching and retrieval, we show the effectiveness of our descriptor, compared to several conventional descriptors.

Scale-invariant features are widely used for image retrieval and shape classification. The curvature of a planar curve is a fundamental feature and it is geometrically invariant with respect it the coordinate system. The curvature-based feature varies in position when multi-scale analysis is performed. Therefore, it is important to recognize the scale in order to detect the feature point. Numerous shape descriptors based on contour shapes have been developed in the field of pattern recognition and computer vision. A curvature scale-space (CSS) representation cannot be applied to a contour fragment and requires the tracking of feature points. In a gradient-based curvature computation, although the gradient computation considers the scale, the curvature is normalized with respect to not the scale but the contour length. The scale-invariant feature transform algorithm that detects feature points from an image solves similar problems by using the difference of Gaussian (DoG). It is difficult to apply the SIFT algorithm to a planar curve for feature extraction. In this paper, an automatic scale detection method for a contour fragment is proposed. The proposed method detects the appropriate scales and their positions on the basis of the difference of curvature (DoC) without the tracking of feature points. To calculate the differences, scale-normalized curvature is introduced. An advantage of the DoC algorithm is that the appropriate scale can be obtained from a contour fragment as a local feature. It then extends the application area. The validity of the proposed method is confirmed by experiments. The proposed method provides the most stable and robust scales of feature points among conventional methods such as curvature scale-space and gradient-based curvature.

A novel fast algorithm for shape matching using statistical features of shape contexts is presented. By pruning the candidate shapes using the moment-based statistical features of shape contexts, the required number of matching processes is dramatically reduced with negligible performance degradation. Experimental results demonstrate that the proposed algorithm reduces the pruning time up to 1/(r·n) compared with the conventional RSC algorithm while maintaining a similar or better performance, where n is the number of sampled points of a shape and r is the number of randomly selected representative shape contexts for the query shape.

An analysis and design of a CMOS differential pair and a common source amplifier for shaping a triangular signal into 0-π/4 segments of sine and cosine waveforms are presented. By multiplexing these two shaped outputs, low distortion full sine and cosine signals can be produced at one fourth the frequency of the triangular input. These two circuits can be combined with one DAC and a phase accumulator to form a compact quadrature direct digital frequency synthesizer (Q-DDFS) suitable for generating low distortion sinusoidal signals at low frequency. The shapers are biased by two current generators specially designed to compensate for process parameter variations. MOS dimensional mismatch is also studied. The analog part of the Q-DDFS is synthesized using 0.18-micron n-well CMOS technology. A simulation shows that the circuit consumes 1.3 mW and can generate 19.96 mV 50 kHz sine and cosine signals with spurious free dynamic range (SFDR) of around 50 dBc from a Q-DDFS running at 1.6 MHz.

The applicability in harsh optical environments, such as dark smog, or strong backlight of ultra-wide band (UWB) pulse radar has a definite advantage over optical ranging techniques. We have already proposed the extended Synthetic Aperture Radar (SAR) algorithm employing double scattered waves, which aimed at enhancing the reconstructible region of the target boundary including shadow region. However, it still suffers from the shadow area for the target that has a sharp inclination or deep concave boundary, because it assumes a mono-static model, whose real aperture size is, in general, small. To resolve this issue, this study proposes an extension algorithm of the double scattered SAR based on a multi-static configuration. While this extension is quite simple, the effectiveness of the proposed method is nontrivial with regard to the expansion of the imaging range. The results from numerical simulations verify that our method significantly enhances the visible range of the target surfaces without a priori knowledge of the target shapes or any preliminary observation of its surroundings.

The Noise Shaper of a full digital amplifier overflows randomly when the Modulation Index of PWM is higher than a certain value. The clipping from the overflow produces an abrupt increase of THD+N that limits MI or the maximum output power. In this paper, we discussed the reason of NS overflow and derived the critical value of MI. We proposed a compensation method for the clipping error and optimized compensation in the audio band. The measurement results show that the proposed method can increase the maximum output power by 6.4% at a 1% THD+N condition. The compensation is more important where the power supply voltage and speaker impedance are difficult to change as that in a car stereo or mobile.

A dual-band patch antenna with a shorting wall and a U-shaped slot is presented in this paper. The shorted-patch is coupled with the aperture slot that is closely placed to the shorting wall for achieving good impedance matching. A U-shaped slot is embedded in the shorted-patch and is located near the radiating edge to yield a dual-band operation. By changing the side slot length of the U-shaped slot, the tunable frequency ratio of the proposed antenna is varied from 1.73 to 2.05.

We describe a parameter estimation method for a target object in an area that sensors monitor. The parameters to be estimated are the perimeter length, size, and parameter determined by the interior angles of the target object. The estimation method does not use sensor location information, only the binary information on whether each sensor detects the target object. First, the sensing area of each sensor is assumed to be line-segment-shaped, which is a model of an infrared distance measurement sensor. Second, based on the analytical results of assuming line-segment-shaped sensing areas, we developed a unified equation that works with general sensing areas and general target-object shapes to estimate the parameters of the target objects. Numerical examples using computer simulation show that our method yields accurate results.

UWB (ultra wide-band) pulse radar is a promising candidate for surveillance systems. The fast SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm is deployed in the application of UWB pulse radar in fields that require real-time operations. However, since the SEABED algorithm uses signals received at multiple locations, this method either needs to scan antennas or to install many antennas. Such systems are inevitably costly and unrealistic for applications such as surveillance. To overcome this problem, a revised SEABED algorithm that estimates unknown target shape based on target motion using only a pair of fixed antennas was developed. However, the method cannot be used when the target moves arbitrarily because it assumes the target motion is parallel to the baseline of the pair of antennas. In this paper, we propose a new UWB radar imaging algorithm that is applicable even for targets with arbitrary motion. The proposed method introduces another antenna which is added to the pair of antennas used in the revised SEABED, and estimates unknown target motion based on the target surface using the three antennas. Next, the proposed method applies the SEABED imaging algorithm to the estimated motion and obtains the target image. Some numerical simulations establishes that the proposed method can accurately estimate the target shape even under severe conditions.

The active shape model (ASM) has been widely adopted by automated bone segmentation approaches for radiographic images. In radiographic images of the distal radius, multiple edges are often observed in the near vicinity of the bone, typically caused by the presence of thin soft tissue. The presence of multiple edges decreases the segmentation accuracy when segmenting the distal radius using ASM. In this paper, we propose an enhanced distal radius segmentation method that makes use of a modified version of ASM, reducing the number of segmentation errors. To mitigate segmentation errors, the proposed method emphasizes the presence of the bone edge and downplays the presence of a soft tissue edge by making use of Dual energy X-ray absorptiometry (DXA). To verify the effectiveness of the proposed segmentation method, experiments were performed with 30 distal radius patient images. For the images used, compared to ASM-based segmentation, the proposed method improves the segmentation accuracy with 47.4% (from 0.974 mm to 0.512 mm).

This paper presents a newly developed small-sized shaped beam base station antenna in order to reduce inter-sector interference for next generation high speed wireless data communication systems. The developed antenna realizes polarization diversity as a single small-sized antenna without decreasing the 3 dB main beamwidth compared with the conventional antenna by applying a newly designed beam shaping method. Furthermore, side sub-reflectors are newly installed in the radome to reduce the antenna beam gain in the direction toward the edge region neighboring the other sectors of the horizontal antenna pattern. By adopting this type of reflector, the diameter of the radome can be minimized at 0.65 λ, which is slightly longer than that of the conventional antenna. Both a computer simulation and a field measurement test based on an actual cellular network were conducted for the purpose of clarifying the validity of the shaped beam antenna. In the results, the CINR at the service area by the shaped beam antenna was 1 dB and 3.5 dB better than that of the conventional antenna at the median and 10% of CDF, respectively. The developed antenna will be expected to contribute to the enhancement of the quality of cellular radio systems in the future.

In order to clarify the physics of contact life time, the relationship between heat capacity of holder and shape of bridge (length and diameter) is discussed in this paper. The AgPd60 alloy is chosen as electrode material. Two holders with different heat capacity are comprised of copper plate and cylinder. The shape of the bridge at the low speed breaking contact is observed by using the high speed digital camera. It was demonstrated that the shape of the bridge is changed by the response and distribution of the temperature.

For improving the nonlinear alignment performance of Active Appearance Models (AAM), we apply a variant of the nonlinear manifold learning algorithm, Local Linear Embedded, to model shape-texture manifold. Experiments show that our method maintains a lower alignment residual to some small scale movements compared with traditional AAM based on Principal Component Analysis (PCA) and makes a successful alignment to large scale motions when PCA-AAM failed.

LCD Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because we get different images. This is caused by possible variations in the image acquisition process including optical factors, non-uniform illumination, random noise, and so on. For this reason, conventional area based defect measuring method has some problems in terms of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome these problems. We utilize volume information which is completely ignored in the area based conventional defect measuring method. We choose a bell shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect for better robustness and consistency.

We propose a character size optimization technique to reduce the number of EB shots of multi-column-cell (MCC) lithographic systems in which transistor patterns are projected with multiple column cells in parallel. Each and every column cell is capable of projecting patterns with character projection (CP) and variable shaped beam (VSB) methods. Seeking the optimal character size of characters contributes to minimizing the number of EB shots and reducing the fabrication cost for ICs. Experimental results show that the character size optimization achieved 70.6% less EB shots in the best case with an available electron beam (EB) size. Our technique also achieved 40.6% less EB shots in the best case than a conventional character sizing technique.