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Aiming at the characteristics of short pulse time and high instantaneous dose rate of pulsed X-ray, a TLD-based few-channel spectrometer is studied. In this paper, the basic structure and principle of the spectrometer are introduced, the absorption plates and detectors of the spectrometer are selected. The energy response matrix of the few-channel spectrometer for single energy photons of different energies is simulated by Monte Carlo method and its influence on the energy resolution of the spectrometer is analyzed. The maximum entropy method is used to verify the pulsed X-ray spectrum resolution. The results show that the TLD-based few-channel spectrometer can be used to measure short pulse and high dose rate pulse X-ray energy spectrum, and it is also suitable for other high dose rate radiation fields.

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Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The tracking-learning-detection (TLD) algorithm is a novel long-term target tracking algorithm, however,the detectors do not fully consider contour changes in the target tracking process, and window-based scanning affects the efficiency. We introduce the evolution mechanism to improve the TLD algorithm based on level set. The multi-scale level set method combines the edge information with the region information ? which improves the adaptation and precision of target tracking while effectively overcomes gray uneven images. According to the test results of the outline,we introduce the motion detection operator of the target direction to estimate the movement direction of the target and its position in the current frame ？ which can reduce the scan window while improving the ability of target identification. Experimental results show that the improved method can enhance the tracking speed,and has stronger adaptability and higher tracking accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Liquid Crystal & Displays is the property of Chinese Journal of Liquid Crystal & Displays and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

TLD algorithm combines tracking, learning and detection simultaneously, so its computation is high. This paper adopted Mean-Shift algorithm to substitute the optical flow tracker of TLD. Considering optical flow tracking has high computation, this optimized algorithm made use of less computation of Mean-Shift to replace optical flow in original TLD. Compared the Bhattacharyya coefficient between target model and target candidate model with the given threshold, it decided whether track failed. Measured similarity between the bounding box returned by Mean-Shift and the bounding box returned by TLD last time, it decided the confidence of the track. If it was failure, the detector would re-initialize the tracker. The experiments show that the optimized algorithm can acquire high robustness and accuracy in long term tracking in video, and it obtains a more rapid tracking speed than original TLD algorithm. [ABSTRACT FROM AUTHOR]