Study On Fractal Characteristics And Correlation Of The Pear Fruit And Leaf

Science and technology are more and more popular in China today, intelligent agriculture and agricultural modernization has also ushered in a new stage, so that the quality of agricultural products and intelligent prediction and classification technology is becoming more and more important. In view of the existing China's fruit export quality is poor, the defects of low prices, using machine vision intelligent feature extraction technology, study on pear fruit quality before level prediction method based on fractal theory. Application of the method has the advantages of rapid, nondestructive, safety, no sample size effect on fruit quality detection.In order to predict the quality of pear, the value of the two images of the pear leaf image and image preprocessing, edge extraction of the leaves and fruits of Rio de la Plata in staples and refinement algorithm, then using fractal theory and fractal theory extracted characteristic parameters of pear leaf the leaves and fruit and dimension is obtained, through the establishment of related simultaneous equations model for crop characteristics, obtained the following conclusions:1.the size and shape of pear leaf size and shape are subject to linear distribution, from a tree in the orchard on the fruit and leaves can infer other pear, pear fruit and growing conditions.2.established a correlation model of pear and leaves, the correlation function between the fruit and leaves:fitting function y=0.7741x-0.9915 perimeter and area of pear leaves; fitting function y=1.096x+4.314 perimeter and area of the leaves of pear; fitting function y= 1.172x-250.2 of leaf area and fruit weight. According to the size, shape and weight distribution of the size and shape of the fruit and leaf of prediction.3. by the relational model and the fitting function of pear fruit and leaf, can predict the leaf size and shape, the measurement for the size and shape of the leaves provide a new method.The results show that, by using the fractal theory to establish prediction model of fruit quality is stable, repeatable, and universal.