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| A Method for Cucumber Identification Based on Iterative -RELIEF and Relevance Vector Machine |
| JIN Li-Zuan, TU Jun, LIU Cheng-Liang |
| (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract To satisfy the requirement of real-time processing and identification accuracy, a method based on iterative-RELIEF relevance vector machine was proposed. In this method, information of image samples is brought into the module of iterative-RELIEF algorithm, which exports a weight for every feature. Then, the information of image samples with weights is brought into the training module of relevance vector machine (RVM). As a result, an image classifier is made, which can be used to predict the classes of unknown pixels of a image containing a cucumber. In the experiment, the rate of right identification is up to 80% or more, while the rate of false identification is lower than 27%, and the ratio of the two is up to 3.0 or more.
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Received: 22 May 2012
Published: 28 April 2013
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