In this paper, we propose a method to estimate the reflectance property from multi-focus images for light source reflected on the object. The blurred information of the light source on the surface is expected to be the practical method to estimate the reflectance property, even though various methods are proposed to estimate the reflectance property. However, the degree of the blurred information will be changed with the position of focus in the camera. Therefore, we introduce the light field camera which can change the position of the focus after the image are captured. In this research, we choose the image where the light source is focused on the object surface. Based on the blurred information of the focused light source, we estimated the reflectance property of the object. The estimated reflectance property is applied to inverse rendering for auto appearance valance.
In this paper, we have developed a feature-based automatic color calibration by using an area-based detection and
adaptive nonlinear regression method. Simple color matching of chartless is achieved by using the characteristic of
overlapping image area with each camera. Accurate detection of common object is achieved by the area-based detection
that combines MSER with SIFT. Adaptive color calibration by using the color of detected object is calculated by
nonlinear regression method. This method can indicate the contribution of object's color for color calibration, and
automatic selection notification for user is performed by this function. Experimental result show that the accuracy of the
calibration improves gradually. It is clear that this method can endure practical use of multi-camera color calibration if
an enough sample is obtained.
We have been developing a rapid proto-typing display system which can verify an appearance of final product in
finishing and painting industry. In this system, it is necessary to measure detail information of hand position and shape to
recognize the worker's instruction. Therefore, we apply a rapid hand measurement which combine a roughly detecting of
hand position and shape by spatial encoding method with IR projection. For detecting of hand position, non-linearity
interval strips are used for detecting objects that are lower than constant height. The interval of strips is devised in
relation to an angle of camera axis to make equal the height in detecting. For detecting of hand shape, the temporal and
spatial encoding pattern is projected only an area of hand position. This measurement is enough rough because our prototyping
display system need only to classify the shape of tracing, touching, pushing, and picking. Therefore, the limited
process with limited area is possible to reconstruct the shape of hand very fast. A practical result shows that the position
and shape recognition is performed about one second; and operator comment that such the time delay doesn't become a
stress as for actual hand operation.
In this paper, we propose a new color matching method between a proof and a target print by using a projection display system based on the spectral color reproduction. In this method, a color of proof is corrected by synthesizing a projection image which is calculated to minimize the color difference between each print. The radiance of the proof and the target print are calculated by using the reflectance of the prints and the radiance from the projector, and we use the method based on the XYZ tristimulus values (colorimetric method) and the spectral values (spectral-based method). We compared the color difference between the colorimetric method and spectral-based method. The average color difference ΔE*94 by using the colorimetric method was 4.00. On the other hand, the color difference used the spectralbased method was 2.13. From these results, we concluded that the spectral-based method is more effective than the colorimetric method to perform the accurate color reproduction by synthesizing the projection color and the proof.
We developed a multi-spectral scanner by using LEDs array with different spectral radiant distribution to measure high accuracy spectral characteristics of printing proof. Five kinds of LEDs were selected from the combination of 40 LEDs on the market to minimize the color difference ΔE*94 between measured and estimated reflectance spectra of 81 kinds of color charts by using polynomial regression and clustering methods. Reflectance spectra of 928 color charts were measured and estimated by using the scanner and the Wiener estimation method. As a result, average color difference ΔE*94 was 1.23 when 81 color data were used to calculate the Wiener estimation matrix.
The final reticle CD uniformity provides us with quantitative information but impracticable one to classify it into each step of the process. We then contrived a new method for quantifying process non-uniformity and classifying it into each of baking and development with properly utilizing resist behaviors in the process.
We firstly tried to quantify baking non-uniformity by utilizing a resist behavior in coating film contraction to baking temperature. A resist film can be used just like a thermo-measuring device if the film contraction occurs significantly enough and linearly to baking temperature.
Secondly, we tried to quantify development non-uniformity by utilizing a resist behavior in film dissolution by development. A resist film can be used as development speed-meter if the film reduction by the development occurs slowly enough and linearly.
This paper describes a novel and convenient technique and its value to quantify process non-uniformity and classify it into resist baking and development.