NIR/MIR dual-sensor machine vision system for online apple stem-end/calyx recognition

摘要

A near-infrared (NIR) and mid-infrared (MIR) dual-camera imaging approach for online apple stem-end/calyx detection is presented in this article. How to distinguish the stem-end/calyx from a true defect is a persistent problem in apple defect sorting systems. In a single-camera NIR approach, the stem-end/calyx of an apple is usually confused with true defects and is often mistakenly sorted. In order to solve this problem, a dual-camera NIR/MIR imaging method was developed. The MIR camera can identify only the stem-end/calyx parts of the fruit, while the NIR camera can identify both the stem-end/calyx portions and the true defects on the apple. A fast algorithm has been developed to process the NIR and MIR images. Online test results show that a 100% recognition rate for good apples and a 92% recognition rate for defective apples were achieved using this method. The dual-camera imaging system has great potential for reliable online sorting of apples for defects.