Discriminant methods of winter pavement conditions
Winter pavement shows various appearances depending upon its kind and
snow conditions. To develop methods for automatically discriminating
its conditions from images captured by CCD camera, various statistical
analyses are applied to different pavement images. One of the results
is shown in the following figure. Six different conditions for two kinds
of pavement are roughly discriminated by means of three parameters of
skewness and contrast derived from probability density functions and
fractal dimension of the pavement images.
 
Discrimination of winter pavement conditions by means of fractal dimension
of the images
(the left and right figures constitute a stereogram).
Near infrared spectral analysis by means of generalized differentiations
Spectra in the near infrared region have properties suitable for analyzing constituents
of complex organic objects such as biomedical tissues, agricultural products
and foods, and hence analyses on the basis of the near infrared spectroscopy
(NIRS) are expanding rapidly into various industries. In this study, to further
improve the performance of NIRS, data processing based on generalized differentiations
is applied. The following figure shows a result of correlation map between
generalized derivative spectra of rice flour and its major constituents (amylose,
moisture and protein). As the derivative order increases, correlation peaks
(portions of dark red) narrow in width, separate into two or more, and/or emerge.

Correlation spectra between generalized derivative spectra
of rice flour and its major constituents (amylose, moisture and protein)
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