ABSTRACT
By using a light-emitting diode as the probing light source and a Shack-Hartmann wavefront sensor as the recorder for the wavefront surface to execute a relative measurement, we present a useful method for determining the small wedge angle and optical homogeneity of a nominally planar glass plate from the wavefront measurements. The measured wavefront surface from the light source was first calibrated to be a horizontal plane before the plate under test was inserted. The wedge angle of the plate can be determined from the inclining angle of the regression plane of the measured wavefront surface after the plate was inserted between the light source and the wavefront sensor. Despite the annoying time-dependent altitude fluctuation in measured wavefront topography, the optical homogeneity of the plate can be estimated from the increment on the average variance of the wavefront surface to its regression plane after the light passes through it by using the Bienaymé formula.
ABSTRACT
We present a noniterative algorithm to reliably reconstruct the spectral reflectance from discrete reflectance values measured by using multicolor light emitting diodes (LEDs) as probing light sources. The proposed algorithm estimates the spectral reflectance by a linear combination of product functions of the detector's responsivity function and the LEDs' line-shape functions. After introducing suitable correction, the resulting spectral reflectance was found to be free from the spectral-broadening effect due to the finite bandwidth of LED. We analyzed the data for a real sample and found that spectral reflectance with enhanced resolution gives a more accurate prediction in the color measurement.
ABSTRACT
Cosmetic industry grows fast in recent years. To reveal the image of dermal structure, it is necessary to apply three-dimensional medical imaging technology. To reduce the invasiveness of laser source on tissues, tissue recognition imaging is proposed to retrieve the intrinsic optical property, namely, the reflection spectrum of every scanned point for imaging. The reflection spectra of main kinds of skin tissue, such as melanin, collagen and hemoglobin, were established as reference database. Broad-band rays were then employed to derive the reflection spectrum of each scanned sample element; the tissue type of the scanned point was identified by cross-correlation of the derived spectrum and the database. In imaging program, all scanned points were filled in with their corresponding tissue color, e.g., black for melanin, white for collagen, or red for hemoglobin, and finally the colored skin tomography resulted. Tissue recognition imaging has merits of easy configuration, low cost, color imaging, high resolution and real non-invasiveness. Substituting LED modules for its spectrometer, tissue recognition imaging is promising to be miniaturized as personal and portable skincare devices, which have great potential in future cosmetic market.
