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首页> 外文期刊>Multimedia Tools and Applications >Performance evaluation of the combination of Compacted Dither Pattern Codes with Bhattacharyya classifier in video visual concept depiction
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Performance evaluation of the combination of Compacted Dither Pattern Codes with Bhattacharyya classifier in video visual concept depiction

机译:视频图像概念描述中压缩抖动模式代码与Bhattacharyya分类器结合的性能评估

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摘要

High dimensionality and multi-feature combinations can have negative effect on visual concept classification. In our research, we formulated a new compacted form which is Compacted Dither Pattern Code (CDPC) as a chromatic syntactic feature for visual feature extraction. The effectiveness of CDPC with Bhattacharyya classifier for irregular shapes based visual concepts depiction is reported in this paper. The proposed technique can reduce feature space and computational complexity while maintaining visual data mining and retrieval accuracy in high standard. Our system was empowered with Bhattacharyya classifier which has improved efficiency by considering one numeric value which is the Bhattacharyya coefficient. Experiments were conducted on various combinations and compared with different visual descriptors and classifiers. The first experiment illustrates the comparison of the CDPC based results with well known feature space reduction classes. The second and third experiments demonstrate the effectiveness of our approach with multiple perspectives of performance measures including various concepts.
机译:高维度和多功能组合可能会对视觉概念分类产生负面影响。在我们的研究中,我们制定了一种新的压缩形式,即压缩抖动模式代码(CDPC)作为视觉特征提取的色度语法特征。本文报道了带有Bhattacharyya分类器的CDPC对于基于不规则形状的视觉概念描述的有效性。所提出的技术可以减少特征空间和计算复杂度,同时保持高标准的可视数据挖掘和检索精度。我们的系统启用了Bhattacharyya分类器,该分类器通过考虑一个数值即Bhattacharyya系数提高了效率。对各种组合进行了实验,并与不同的视觉描述符和分类器进行了比较。第一个实验说明了基于CDPC的结果与众所周知的特征空间缩减类的比较。第二和第三个实验从绩效衡量的多个角度(包括各种概念)证明了我们方法的有效性。

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