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Second order Statistical Texture Features from a New CSLBPGLCM for Ultrasound Kidney Images Retrieval

机译:新的CSLBPGLCM用于超声肾脏图像检索的二阶统计纹理特征

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Normal 0 false false false This work proposes a new method called Center Symmetric Local Binary Pattern Grey Level Co-occurrence Matrix (CSLBPGLCM) for the purpose of extracting second order statistical texture features in ultrasound kidney images. These features are then feed into ultrasound kidney images retrieval system for the point of medical applications. This new GLCM matrix combines the benefit of CSLBP and conventional GLCM. The main intention of this CSLBPGLCM is to reduce the number of grey levels in an image by not simply accumulating the grey levels but incorporating another statistical texture feature in it. The proposed approach is cautiously evaluated in ultrasound kidney images retrieval system and has been compared with conventional GLCM. It is experimentally proved that the proposed method increases the retrieval efficiency, accuracy and reduces the time complexity of ultrasound kidney images retrieval system by means of second order statistical texture features.
机译:正常0错误错误错误本工作提出了一种新方法,称为中心对称局部二进制图案灰度共现矩阵(CSLBPGLCM),目的是提取超声肾脏图像中的二阶统计纹理特征。然后将这些功能输入到超声肾脏图像检索系统中,以用于医疗应用。这种新的GLCM矩阵结合了CSLBP和传统GLCM的优势。此CSLBPGLCM的主要目的是通过不仅仅累加灰度级,而是在其中合并另一个统计纹理功能来减少图像中的灰度级数量。所提出的方法在超声肾图像检索系统中进行了谨慎评估,并已与常规GLCM进行了比较。实验证明,该方法利用二阶统计纹理特征提高了超声肾脏图像检索系统的检索效率,准确性,降低了时间复杂度。

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