Design and analysis of various bidirectional 2DPCAs in feature partitioning framework

Sahoo, Tapan Kumar; Banka, Haider; Negi, Atul

doi:10.1007/s11042-021-10535-6

Cited by 4 publications

(2 citation statements)

References 43 publications

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“…To extract more structure information from images, Titijaroonroj et al [24] and Sahoo et al [25,26] made improvements on the traditional 2DPCA by utilizing it on subimages of the original image. The subimages are generated by sliding a window on the original image or by partitioning the original image into blocks.…”

Section: Related Workmentioning

confidence: 99%

“…Bilateral algorithms Zhang et al [21] (2D) 2 PCA Kong et al [22] Generalized 2DPCA Yang et al [23] RC2DPCA Subimages Titijaroonroj et al [24] RCM-2DPCA Sahoo et al [25] ESIMPCA, EFLPCA Sahoo et al [26] Bi-ESIMPCA, Bi-EFLPCA Robust and sparse modelling Li et al [27] 2DPCA-L1 Wang et al [28] non-greedy 2DPCA-L1 Yang et al [29] 2DPCA-T 1 Wang and Wang [30] 2DPCAL1-S Wang [31] G2DPCA Rotational invariance Gao et al [34] R 1 -2DPCA Li et al [35] F-2DPCA Gao et al [36] Angle-2DPCA Wang and Li [37] Area-2DPCA Wang et al [38] Cos-2DPCA Bi et al [39] ROMCA-2DPCA Razzak et al [40] ORPCA Mi et al [41] 2,p -2DPCA Zhou et al [42] GC-2DPCA Kuang et al [43] F p -2DPCA Zhou et al [44] BA2DPCA Bi et al [45] 2,p -SB-2DPCA Color image processing Xiang et al [46] C-2DPCA Jia et al [47] 2D-QPCA Xiao and Zhou [48] QRR-2D-QPCA Wang et al [49] F-2D-QPCA Jia et al [50] G-2D-QPCA Zhao et al [ 2DPCA-Net Li et al [57] L1-2DPCA-Net…”

Section: Category Bibliography Algorithmmentioning

confidence: 99%

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Fusion of Bilateral 2DPCA Information for Image Reconstruction and Recognition

et al. 2022

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Being an efficient image reconstruction and recognition algorithm, two-dimensional PCA (2DPCA) has an obvious disadvantage in that it treats the rows and columns of images unequally. To exploit the other lateral information of images, alternative 2DPCA (A2DPCA) and a series of bilateral 2DPCA algorithms have been proposed. This paper proposes a new algorithm named direct bilateral 2DPCA (DB2DPCA) by fusing bilateral information from images directly—that is, we concatenate the projection results of 2DPCA and A2DPCA together as the projection result of DB2DPCA and we average between the reconstruction results of 2DPCA and A2DPCA as the reconstruction result of DB2DPCA. The relationships between DB2DPCA and related algorithms are discussed under some extreme conditions when images are reshaped. To test the proposed algorithm, we conduct experiments of image reconstruction and recognition on two face databases, a handwritten character database and a palmprint database. The performances of different algorithms are evaluated by reconstruction errors and classification accuracies. Experimental results show that DB2DPCA generally outperforms competing algorithms both in image reconstruction and recognition. Additional experiments on reordered and reshaped databases further demonstrate the superiority of the proposed algorithm. In conclusion, DB2DPCA is a rather simple but highly effective algorithm for image reconstruction and recognition.

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Section: Related Workmentioning

confidence: 99%