利用图像直方图多阈值分割实现LED芯片焊盘快速检测研究

Research on Fast Detection of LED Chip Solder Pads Using Image Histogram Multi-threshold Segmentation

摘要:

针对LED芯片下底部填充胶贴合情况焊盘检测，研究了一种利用直方图曲线极小值点作为分割阈值的灰度图像多阈值分割方法；通过对X-ray检测机采集的LED芯片下底部填充胶贴合情况图像直方图曲线的平滑处理和条件判断，寻找满足预期的波峰波谷，将对应的极小值点作为分割阈值，实现图像的多阈值快速分割方法；相比OTSU方法多阈值分割和区域生长算法，该方法计算复杂度较低，在LED芯片下底部填充胶贴合情况焊盘的识别和分割过程中，分割耗时不到OTSU方法和区域生长算法的百分之一，分割效果相比OTSU方法更好，而且针对图像整体灰度的差异，具有较强的自适应性，满足工业生产线对高UPH的要求；表明该方法在处理直方图曲线具有明显波峰波谷的图像分割时具有显著的速度优势。

Abstract:

Regarding the inspection of solder pads for the bottom filling adhesive bonding of LED chips. This paper investigates a method for the multi-threshold segmentation of grayscale image using the local minimum points of histogram curve as the segmentation threshold. By smoothing the histogram curve and judging the conditions, the expected peaks and valleys are identified, and the corresponding minimum points are used as segmentation thresholds to achieve fast multi threshold image segmentation. Compared with the OTSU method for multi threshold segmentation and region growing algorithm, this method has lower computational complexity. In the identification and segmentation process of solder pads under LED chips with bottom filling adhesive bonding, the segmentation time is less than one percent of that of the OTSU method and region growing algorithm. This segmentation effect is better than the OTSU method. Moreover, it has strong adaptability to the overall grayscale differences of images, meeting the requirements for high UPH (Units Per Hour) in industrial production lines. This indicates that the method has a significant speed advantage in segmenting images with obvious peaks and valleys in the histogram curve.