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An Improved Method for Singularity Detection of Fingerprint Images

机译:一种改进的指纹图像奇异性检测方法

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摘要

It is important for automatic fingerprint identification system to detect singularities of fingerprint images accurately and reliably. This paper proposes an improved method for singularity detection of fingerprint images. First, a fingerprint image is divided into non-overlapping blocks with the same size, the column which the core belongs to is acquired by detecting the horizontal part of the ridge, and then the row which the core belongs to is got. Also, the column and the row, which the delta belongs to, are acquired according to those acute variable ridge directions of left and right parts of the delta. Then, singularities are detected with Poincare index within the block image which the column and the row belong to. If no singularity is detected in the block image, search area is expanded to detect. At worst, the whole image is searched. Experimental results indicate that the improved method is effective and, even to low quality image, it still can detect the singularities reliably.
机译:准确,可靠地检测指纹图像的奇异性对于自动指纹识别系统至关重要。本文提出了一种改进的指纹图像奇异性检测方法。首先,将指纹图像分成相同大小的非重叠块,通过检测脊的水平部分来获取核芯所属的列,然后得到核芯所属的行。而且,根据三角洲左右部分的那些锐变脊方向,获取三角洲所属的列和行。然后,利用列和行所属的块图像内的庞加莱指数检测奇异性。如果在块图像中未检测到奇异点,则扩展搜索区域以进行检测。最糟糕的是,将搜索整个图像。实验结果表明,改进的方法是有效的,即使对于低质量的图像,仍然可以可靠地检测到奇异点。

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