Machine vision technique is playing an increasingly important role in monitoring plant growth. The identification of good or bad status of growing plant requires specific features such as color, length, and solidity of stems. This paper addresses recognition of growing status of the green bean sprout. For preprocessing, RGB color images are converted to hue-saturationintensity (HSI) images, and then, principal component analysis (PCA) is applied to reduce the high dimensionality of image data.

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... inally, linear discriminant analysis (LDA) recognizes whether the growing status is good or bad. In the experiments, the images of the green bean sprouts growing in jars are acquired for 6 consecutive days. The correct classification rates are compared between PCA only process and LDA combined with PCA. The experimental results show PCA+LDA can achieve more than 93.3% average accuracy after 3 days.