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首页> 外文期刊>Journal of Real-Time Image Processing >Sorting of rice grains using Zernike moments
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Sorting of rice grains using Zernike moments

机译：使用Zernike矩对米粒进行分类

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Two important factors that determine the efficiency and reliability of a rice sorting machine are the overall processing speed and the classification accuracy. In this paper, an efficient rice sorting process which uses a subset of Zernike moments (ZM) and a multilayer per-ceptron is presented. Since the falling rice grains during sorting process can be in any orientation, a rotational invariant feature set is crucial in this application. Hence, the set of ZM with its inherent rotational invariance property is chosen in this context. Nevertheless, one of the main drawbacks of ZM in real-time application is its long computation time. To overcome this, a subset of ZM is selected from its original full set of 12 orders, using the combination of fuzzy ARTMAP and genetic algorithm. To further reduce the computation time, the combination of q-recursive method and Zernike polynomials' inherent symmetry property is utilized. Hence, the processing time of the subset of ZM is significantly reduced by almost 67% while maintaining the classification accuracy as compared to computing the original full set of ZMs.
机译：决定米分拣机效率和可靠性的两个重要因素是总体处理速度和分类精度。在本文中，提出了一种有效的大米分选过程，该过程使用Zernike矩（ZM）的子集和多层每个感知器。由于分选过程中落下的米粒可以处于任何方向，因此旋转不变特征集在此应用中至关重要。因此，在这种情况下选择具有其固有的旋转不变性的ZM集。尽管如此，ZM在实时应用中的主要缺点之一是计算时间长。为了克服这个问题，使用模糊ARTMAP和遗传算法相结合，从ZM的原始全套12阶中选择ZM的子集。为了进一步减少计算时间，结合了q递归方法和Zernike多项式的固有对称性。因此，与计算原始全套ZM相比，ZM子集的处理时间显着减少了近67％，同时保持了分类精度。

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