KEYWORDS: Sensors, Radon transform, Digital signal processing, Mobile devices, Detection and tracking algorithms, Image processing, Image segmentation, System on a chip, Lanthanum, Hough transforms
We propose a local bar-shaped structure detector that works in real time on high-resolution images.
It is based on the Radon transform. Specifically in the muti-scale variant, which is especially fast because it works in integer mathematics and does not use interpolation.
The Radon transform conventionally works on the whole image, and not locally. In this paper we describe how by stopping at the early stages of the Radon transform we are able to locate structures locally.
We also provide an evaluation of the performance of the algorithm running on the CPU, GPU and DSP of mobile devices to process at acquisition time the images coming from the device's camera.
Wave Front Phase Imaging (WFPI), a new wafer geometry technique, is presented, that acquires 7.65 million data points in 5 seconds on a full 300mm wafer providing lateral resolution of 96µm. The system has high repeatability with root-mean-square (RMS) standard deviation (σRMS) in the single digit nm for the global wafer geometry and in the sub ångström (Å = 10-10 m) range for the full-wafer nanotopography for both 200mm and 300mm blank silicon wafer. WFPI can collect data on the entire wafer to within a single pixel, in our case 96µm, away from the wafer edge roll off. The flatness of the silicon wafers used to manufacture integrated circuits (IC) is controlled to tight tolerances to help ensure that the full wafer is sufficiently flat for lithographic processing. Advanced lithographic patterning processes require a detailed map of the wafer shape to avoid overlay errors caused by depth-of-focus issues. We present WFPI as a new technique with high resolution and high data count acquired at very high speed.
Wave Front Phase Imaging (WFPI) is used to measure the stria on an artificial, transparent plate made of Schott N-BK7® glass material by accurately measuring the Optical Path Difference (OPD) map. WFPI is a new technique capable of reconstructing an accurate high resolution wave front phase map by capturing two intensity images at different propagation distances. An incoherent light source generated by a light emitting diode (LED) is collimated and transmitted through the sample. The resultant light beam carries the wave front information regarding the refraction index changes inside the sample1. Using this information, WFPI solves the Transport Intensity Equation (TIE) to obtain the wave front phase map. Topography of reflective surfaces can also be studied with a different arrangement where the collimated light beam is reflected and carrying the wave front phase, which again is proportional to the surface topography. Three Schott N-BK7® glass block samples were measured, each marked in which location the wave front phase measurement will be performed2. Although WFPI output is an OPD map, knowing the value of refractive index of the material at the wavelength used in the measurements will lead to also knowing the thickness variations of the plate.
The flatness of the silicon wafers used to manufacture integrated circuits (IC) is controlled to tight tolerances to help ensure that the full wafer is sufficiently flat for lithographic processing. Advanced lithographic patterning processes require a detailed map of the wafer shape to avoid overlay errors caused by depth-of-focus issues. A large variety of new materials are being introduced in Back-End of Lines (BEOL) to ensure innovative architecture for new applications. The standard in-line control plan for the BEOL layer deposition steps is based on film thickness and global stress measurements which can be performed on blanket wafers to check the process equipment performance. However, the challenge remains to ensure high performance metrology control for process equipment during high volume manufacturing. With the product tolerance getting tighter and tighter and architecture more and more complex, there is an increasing demand for knowledge of the wafer shape. In this paper we present Wave Front Phase Imaging (WFPI), a new wafer geometry technique, where 7.65 million data points were acquired in 5 seconds on a full 300mm wafer enabling a lateral resolution of 96μm.
Radon transform, and more specifically the multiscale Discrete Radon Transform, is a valuable tool to find straight structures on images.
But the straight lines that DRT finds are those traversing completely the image, and hence DRT is unable to detect non-straight structures.
That limitation is normally adressed by evaluating Radon transform on non-overlapped subsquares of the image. In this work we will show that the initial partial transform stages of multiscale DRT contain enough information to detect non-straight edges.
By stopping on initial stages of an already linearithmic transform that can be executed on integer arithmethics, the proposed method is found to be much faster than its alternatives.
We will show its ability to process images at video acquisition rate on mobile phones.
Points of view generation allows to create virtual views between two or more cameras observing a scene. This field receives attention from multimedia markets, because sufficiently realistic points of view generation should allow to navigate freely between otherwise fixed points of observation. The new views must be interpolated between sampled data, aided by geometrical information relating real cameras poses, objects in the scene and desired point of view. Normally there are several steps involved, globally known as Structure from Motion (SfM) method. Our study focuses on the last stage; image interpolation based on the disparities between known cameras. In this paper, a new method is proposed that uses depth maps generated by a single camera, named SEBI, allowing a more efficient filling in presence of occlusions. Occlusions are considered during interpolation, creating an occlusion-map and an uncertainty-map using the depth information that SEBI cameras provide.
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