An Improved SURF Algorithm with FREAK Descriptor for BGA Component Image Stitching

F. Chen, Jielin Deng
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引用次数: 1

Abstract

This paper presents an image stitching method of BGA component for industrial operation. The mounter is the core equipment of the surface mount system, and it currently has no way to place components larger than the camera's field of view. Therefore, a high-speed image stitching method of BGA component is still not available. In this method, the hu invariant moment is used to determine the overlapping area of the image and reduce the range of feature point extraction. After obtaining the feature points, the differences between the SIFT (Scale Invariant Features Transform) algorithm, the SURF (Speeded Up Robust Features) algorithm and the improved SURF algorithm are compared. The improved SURF algorithm combines the SURF feature extraction method and the FREAK (Fast Retina Keypoint) descriptor is developed. After the feature points are processed by BFMather matching and RANSAC algorithm, the image transformation matrix of the two images is calculated. Finally, the perspective transformation is performed on the image to complete the image stitching. This image stitching method is shown to be simple and effective for high-speed industrial application. The procedure taken can be extended to other similar IC component and to other machine.
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一种改进的带有FREAK描述符的SURF算法用于BGA分量图像拼接
提出了一种适用于工业操作的BGA分量图像拼接方法。贴片机是表面贴装系统的核心设备,目前还没有办法放置比相机视场更大的组件。因此,目前还没有一种基于BGA分量的高速图像拼接方法。该方法利用hu不变矩来确定图像的重叠区域,减小特征点提取的范围。在获得特征点后,比较了SIFT (Scale Invariant Features Transform)算法、SURF (accelerated Robust Features)算法和改进SURF算法的差异。将SURF特征提取方法与FREAK (Fast Retina Keypoint)描述符相结合,提出了改进的SURF算法。对特征点进行BFMather匹配和RANSAC算法处理后,计算两幅图像的图像变换矩阵。最后对图像进行透视变换,完成图像拼接。该图像拼接方法简单有效,适合高速工业应用。所采取的程序可以推广到其他类似的集成电路元件和其他机器。
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