基于彩色图像的梨表面缺陷提取方法

随着我国改革开放步伐的加大,梨等农产品的深加工对提升出口梨果质量水平、提高出口规模和增加国民收入具有重大意义.经实践检验,采用数字图像处理技术对水果进行外观品质分级,具有速度快、准确度高等特点,并可广泛应用于多种水果和蔬菜的分级过程中.目前,国内针对梨的外观品质分级的研究相对较少,梨表面颜色多,斑点、果锈等干扰多,导致难以进行准确的缺陷识别是重要的原因之一.由于使用传统外观缺陷提取方法难以获得良好的效果,所以提出了一种新的基于彩色图像的缺陷提取方法,以期在多种情况的梨表面缺陷提取操作中获得准确率高、鲁棒性强等效果.对该方法进行了一些测试,取得了积极的效果.

Pear Surface Defect Extraction Method Based on Color Image

With the increasing pace of China＇s reform and opening policies,the pear and other agricultural products deep processing is of great significance for enhancing the quality of exports,increasing the export quantum and export earnings.Practice proves that using the digital image processing technology to classify the fruit appearance quality has the features of fast speed and high accuracy,which is widely used in the processes of classifying a variety of fruits and vegetables.At present,the domestic study of the pear appearance classification is relatively rare.It is hard to detect the deflect accuracy owing to the variety of surface colors,spots,rust and other interference on the pear surface.This paper presents a new defect extraction method based on the color image so as to obtain high accuracy and strong Lu Stick effects in various situations of pear surface defect extraction operation.In conclusion,the author carried out some tests on the method and achieved positive results.