Many structures in aerospace, semiconductor and precision engineering are multi-layer in nature. Examples include Low
Temperature Co-Fire Ceramic (LTCC), PCBA, stacked IC, Through-Silicon-Via and composite materials for aircraft
wings. Segmentation of each internal layer in any orientation is essential for layer alignment as well as delamination,
disbond and warpage analysis. In this paper we propose a RDHT (Reduced Dimension Hough Transformation) for
automatic layer detection. Instead of segmenting internal surfaces at voxel level, correlation based edge operator is
applied to extract features in 3D space whereby the likelihood of any planar structure is associated with the number of
features on a specific plane. We use Randomized Hough Transform to map 3D features in three one dimensional
accumulators plus one verification accumulator to reduce Hough space dimension. The RDHT has been successfully
applied to various objects to reveal internal planar structures. For a CT result with a 512×512×512 cube, the feature
detection takes 30 seconds and the subsequent layer separation takes 12 seconds (laptop with Intel dual core 1.6G). We
demonstrate that the algorithm can segment all 16 layers of a stacked IC with an accuracy of 0.5 voxel.
A study on Chemical Oxygen Demand (COD) measuring method is reported, in which the COD value is measured by an integrated liquid drop monitor sensor without any reagent and chemical treatment. The integrated drop sensor consists of a liquid head, an integrated fiber sensor and a capacitor sensor. The capacitor sensor is composed of a drop head and a ring electrode. As the part of the drop head, the outline of the drop will be changed during the drop forming, which result in the variation of the capacitance. The fiber sensor is composed of two fibers that are positioned into the liquid drop. The light signal goes into the liquid drop from one fiber and out from the other one. A unique fingerprint of the liquid drop can be got by the data processing. The matching between the COD value of a liquid and the codes of the fingerprints in the database are presented and discussed.
This paper describes a multispectral liquid drop analyzer for liquid chemical and physical properties analysis. Liquid drops formed at the tip of a liquid head are measured in parallel by a fiber sensor and a capacitive sensor. The fiber sensor works as follows: multispectral light sources are injected into the drop through an optical fiber and the total internal reflections and absorptions are detected by a photodetector. By combining fiber and capacitive sensor outputs, a drop speed independent one-dimensional waveform (liquid fingerprint) is generated. Liquid surface tension, refractive index and di-electric constant can be estimated from the fingerprint. To compare two fingerprints, the sensor outputs are normalized to have the same unit of measurement and drop starting position. After that, a reference liquid based calibration is applied to correct of fingerprint distortion due to variations in environment conditions, such as changes in temperature and humidity. Finally, a normalized correlation algorithm analyses the fingerprint difference. The repeatability and sensitivity of the system are demonstrated using different liquid samples. On-line applications show that the analyzer is able to detect 2% change in alcohol density.
This paper reports our preliminary investigation of developing an optically coupled CCD x-ray imaging system for digital x-ray fluoroscopy. The limitations of an image intensifier, TV camera based fluoroscopy are discussed. The contrast sensitivity and contrast-detail deductibility of a lens coupled CCD prototype was compared with an image- intensifier, TV camera based fluoroscopy. The results indicated that a well designed coupled CCD can be x-ray quantum noise limited, and it offers better contrast and resolution than the investigated image-intensifier, TV camera fluoroscopy systems.
Conference Committee Involvement (4)
Optical Metrology and Inspection for Industrial Applications II
5 November 2012 | Beijing, China
Optical Metrology and Inspection for Industrial Applications
18 October 2010 | Beijing, China
Optical Inspection and Metrology for Non-Optics Industries
3 August 2009 | San Diego, California, United States
Optomechatronic Sensors, Actuators, and Control
25 October 2004 | Philadelphia, Pennsylvania, United States