Optical tomography, as a novel technique developed recently, has drawn more and more interest among imaging of biology tissue, astronomy and industrial process monitoring, and so on. Extinction method is one of traditional measurement for particle concentration, which can be improve a novel optical measurement with computed tomography(CT) to reconstruct image of particle concentration distribution. In this paper, the theoretical model of extinction optical tomography was presented, the relationship between geometric structure of optical array sensors and section drawings of measured area was analyzed, and so did between the structure and spatial resolution. In experiments, 8x8 orthogonal array of optical sensors with two-directions projection are used for flow imaging by means of FBP, which is for capturing movement track of a glass canaliculus with arenaceous quartz inside in a section. Furthermore, image reconstructions based on optical array sensors with two-directional angles and four-directional angles are simulated numerically and some significant results can be found from the simulated results.

A new method of automatic reading of high-precision pointer meter is introduced. first, the color image was transformed to gray image; secondly, the area of dial plate was segmented by threshold value and projection; thirdly, the pointer needle was located using dot-goniometry; then the graduation and reflector were located by arc projection; finally, the pointer needle value is recognized automatically. Key Words: pointer meter automatic recognition image processing locate pointer needle straight line detection using dot-goniometry

This paper studies an intelligent inference model embedded parallel competitive neural network, and implements the simulation of Traditional Chinese Medicine (TCM) experts in diagnosis and inference process, by integrating fuzzy neural networks(FNN) technology, image processing and recognition technology, data mining technology and extension thought. The results of complex TCM diagnosis and inference process show that the intelligent inference model studied in this paper can preferably be applied to TCM differentiation of symptoms and signs.

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