基于隐马尔科夫模型的苹果分级方法研究

提出了一种基于隐马尔科夫模型的苹果分级方法。以3种不同颜色和形状的苹果为研究对象,提取苹果的六角锥体模型(HSV)作为苹果的颜色特征,提取苹果Hu不变矩作为苹果的形状特征,将这些特征量采用Lloyd算法编码,并将它们作为隐马尔科夫模型(HMM)的输入。依据HMM模式识别方法,对不同颜色和形状的苹果进行了分类识别,进而完成苹果分级。试验表明,该方法完成的分级识别率为100%。

Study on method of apple grading based on hidden Markov model

In order to adapt to the request of apple grading technology, a classification method for apple grading was proposed based on hidden Markov model (HMM). Three different colors and shapes of apples were studied. The hexagonal pyramid model (HSV) was extracted as the color features of the apple, and the Hu invariant moment was extracted as shape features of the apple. These features of the apple were coded by Lloyd algorithm, which was used as the inputting of HMM. According to the HMM pattern recognition method, the different colors and shapes of apples were identified and classified, and then the apple grading was completed. The tests showed that the apple grading results were correct by the proposed method.