This paper describes the development of a fiber-optic confocal probe suitable to measuring the central thickness of highcurvature
small-diameter optical ball lenses. The confocal probe utilizes an integrated camera that functions as a realtime
apex-sensing device. An additional camera is used to monitor the shape of the reflected light beam. Placing the
instrument sensing spot off-center from the apex will produce a non-circular image at the camera plane that closely
resembles an ellipse for small displacement. By analyzing the shape of the reflected light spot, we are able to precisely
determine the focus point of the confocal probe relative to the apex point to better than 2-μm precision for ball lenses
with diameters in the range of 3 – 10 mm. The proposed confocal probe offers a low-cost alternative technique for
quality control of ball lenses during the manufacturing process.
The amount of light is an important issue in several scenarios ranging from scenic design, light pollution study,
illumination engineering, and agriculture. It is typically determined by using a portable digital light or lux meter. By
realizing that the proliferation of cell phones is currently tremendous, this paper proposes for the first time a low-cost cell
phone based digital light meter. Our innovative idea comes from the fact that the digital camera built into the cell phone is functioned as a two-dimensional light sensitive device and the captured image can be made diffuse. In this way, the diffused image is correlated to the corresponding light level by the built-in microprocessor of the cell phone and our specific algorithm embedded. Our experiment using a typical cell phone embedded with a digital camera and our JAVA program will be discussed.
Surface plasmon resonance (SPR) sensors with spectral interrogation provide a high refractive index resolution, a large
dynamic range and a fixed optical detection module. In this work, we propose a new spectral detection unit that uses only
one spectrometer to measure the SPR spectrum from multiple sensing spots rapidly and serially without any mechanical
movement. This spectral detection unit is designed based on a spatial light modulator (SLM) configured as a
programmable optical aperture for the spectrometer. To demonstrate this concept, a five-channel SPR sensor was built
based on the proposed multichannel detection unit and we evaluated the device performance using a refractive index test.
The average device refractive index resolution was 1.4 x 10-6 refractive index units (RIU).
Interrogation is an important step for seeking truth from the suspect. With the limit of the intrusive nature of the current
polygraph, we show here a highly-sought-after non-intrusive lie detection system with a user-friendly interface called
TAD2. The key idea behind our TAD2 is based on the analysis of far-infrared data obtained remotely from the periorbital
and nostril areas of the suspect during the interrogation. In this way, measured change in skin temperature around two
periorbital areas is converted to a relative blood flow velocity while a respiration pattern is simultaneously determined
from the measured change in temperature around the nostril region. In addition, TAD2 is embedded with our automatic
baseline assignment that is used for distinguishing the subject's response into normal or abnormal stage. In our TAD2,
the officer can choose to perform one of the three standard lie detection tests, namely, a modified zone comparison test, a
modified general question test, and an irrelevant & relevant test. Field test results from suspects in real crime cases are
discussed.
This paper studies the use of a combination of Haar-like features and a cascade of boosted tree classifiers embedded in a
widely used OpenCV for face detection in thermal images. With 2013 positive and 2020 negative 320×240-pixel thermal
images for 20 training stages on three window sizes of 20×20, 24×24, and 30×30 pixels, our experiment shows that these
three windows offer similar hit and false alarm rates at the end of the training section. Larger windows also spend much
more time to train. During our testing, the 30×30-pixel window provides measured best hit and false
rejection/acceptation rates of 93.4% and 6.6%, respectively, with a measured slowest detection speed of 19.6 ms. A 5-ms
improvement in the measured detection speed with a slightly lower hit rate of 92.1% is accomplished by using the
24×24-pixel window. These results verify that the combination of Haar-like features and a cascade of boosted tree
classifiers is a promising technique for face detection application in thermal images.
We have developed a non-invasive thermal image analyzer for deceptive detection (TAD2) where the far-infrared data
around the periorbital and nostril areas are simultaneously analyzed. Measured change in maximum skin temperature
around two periorbital regions is converted to a relative blood flow velocity. A respiration pattern is also simultaneously
determined via the ratio of the measured maximum and minimum temperatures in the nostril area. In addition, our TAD2
employs a simple normalized cross correlation scheme to independently track locations of the two periorbital and nostril
areas. Our field case study from 7 subjects in two real crime scenes and with the use of our baseline classification criteria
shows two-fold improvement in classification rate compared to our analysis using either the periorbital or nostril area
alone.
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