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Absfruct-This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The WGMP is the problem of finding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs an analytic, instead of a combinatorial or iterative, approach to the optimum matching problem of such graphs. By using the eigendecompositions of the adjacency matrices (in the case of the undirected graph matching problem) or some Hermitian matrices derived from the adjacency matrices (in the case of the directed graph matching problem), a matching close to the optimum one can be found efficiently when the graphs are sufficiently close to each other. Simulation experiments are also given to evaluate the performance of the proposed method.

In conventional functional near-infrared spectroscopy (fNIRS), systemic physiological fluctuations evoked by a body's motion and psychophysiological changes often contaminate fNIRS signals. We propose a novel method for separating functional and systemic signals based on their hemodynamic differences. Considering their physiological origins, we assumed a negative and positive linear relationship between oxy- and deoxyhemoglobin changes of functional and systemic signals, respectively. Their coefficients are determined by an empirical procedure. The proposed method was compared to conventional and multi-distance NIRS. The results were as follows: (1) Nonfunctional tasks evoked substantial oxyhemoglobin changes, and comparatively smaller deoxyhemoglobin changes, in the same direction by conventional NIRS. The systemic components estimated by the proposed method were similar to the above finding. The estimated functional components were very small. (2) During finger-tapping tasks, laterality in the functional component was more distinctive using our proposed method than that by conventional fNIRS. The systemic component indicated task-evoked changes, regardless of the finger used to perform the task. (3) For all tasks, the functional components were highly coincident with signals estimated by multi-distance NIRS. These results strongly suggest that the functional component obtained by the proposed method originates in the cerebral cortical layer. We believe that the proposed method could improve the reliability of fNIRS measurements without any modification in commercially available instruments.

The image of an opaque object is created by observing the reflection of the light incident on its surface. The dichromatic reflection model describes the surface reflection as the sum of two components, diffuse and specular terms. The specular reflection component is usually strong in its intensity and polarized significantly compared to the diffuse components. On the other hand, the intensity of the diffuse component is weak and it tends to be unpolarized except near occluding contours. Thus, the observation of an object through a rotating polarizer approximately yields images containing constant diffuse component and specular component of different intensity. In this paper, we show that diffuse and specular components of surface reflection can be separated as two independent components when we apply Independent Component Analysis to the images observed through a polarizer of different orientations. We give a separation simulation of artificial data and also give some separation results of real scenes.

Functional near-infrared spectroscopy has the potential to easily detect cerebral functional hemodynamics. However, in practical fNIRS measurements, a subject's physical or systemic physiological activities often cause undesirable artifacts. Such activities can be evoked even by task execution. In this case, observed artifacts may correlate strongly with the task sequence, and it is difficult to eliminate them by conventional signal filtering techniques. We present a theoretical analysis and Monte Carlo simulations of layered media in which both scattering and absorption changes occur, and show that a multidistance probe arrangement is effective in removing artifacts and extracting functional hemodynamics. The probe arrangement is determined based on simulation results. Artifacts induced by nonfunctional tasks (body tilting, head nodding, and breath holding) are clearly observed when a conventional method is used; such artifacts are appreciably reduced by the proposed method. Signals evoked by single-sided finger movements are observed at both hemispheres when we use a conventional method. On the other hand, localized signals at the primary motor area are observed by the proposed method. A statistically significant increase in oxygenated hemoglobin and decrease in deoxygenated hemoglobin are simultaneously observed at the contralateral primary motor area.