针对家庭农场及小规模营销的需要,设计了基于机器视觉的小型农产品分选机。农产品在平胶带上形成多通道阵列式输送,以DSP作为机器视觉单元的核心,采集一帧图像可分析多个通道,并根据农产品的形状、颜色等图像特征进行分选。在水平输送速度为9.2cm/s、农产品输送间隔为16cm、4通道并行输送的条件下,选用核桃、红枣及栗子3种农产品进行了分选机性能测试。试验表明,机器能够可靠工作;核桃、红枣和栗子的分选准确性分别为91.66%、94.79%和97.39%;分选速度达8800个/h。因此采用DSP芯片作为小型分选机的机器视觉核心是可行的,可以为农产品分选机的小型化、低成本提供技术支持。
Quality grading is usually performed to agricultural products after harvesting by sorting machines with existing problems including large size, high price, etc. To meet the demands of family farming and small scale marketing, we designed a small-scale agricultural product sorting machine based on machine vision. Agricultural products were conveyed to the multi-channel conveyer belt and sorted with features including shape, color and etc. by the DSP-cored machine. Quality of products in separated channels can be analyzed with single frame image. Performance tests were conducted with walnuts, red dates and chestnuts selected as testing objects to the sorting machine. The test parameters including horizontal transmission speed, product transmission interval, parallel transmission channel amount were set to 9.2 cm/s, 16 cm and 4, respectively. The test results indicated that the sorting machine performed reliably with selection accuracy rate of 91.66% , 94.79% and 97.39% in walnuts, red dates and chestnuts respectively, with culling speed of approximately 8800 products per hour. Hence feasibility was proved that DSP could be performed as the machine vision core component of small-scale intelligent sorting machine, which provided technical supports of miniaturization and low cost for agricultural product