scholarly journals A Comparative Study of Various Inclusive Indices and the Index Constructed By the Principal Components Analysis

2007 ◽  
Author(s):  
S. K. Mishra
Keyword(s):  
Comparative Study ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Components Analysis

scholarly journals Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures DOI: 10.5585/exacta.v8i2.2000

Exacta ◽  
2010 ◽  
Vol 8 (2) ◽  
pp. 225-235
Author(s):  
Fábio Henrique Pereira ◽  
Elesandro Antonio Baptista ◽  
Nivaldo Lemos Coppini ◽  
Rafael Do Espírito-Santo ◽  
Ademir João de Oliveira
Keyword(s):  
Image Compression ◽  
Comparative Study ◽  
Principal Components Analysis ◽  
Principal Components ◽  
High Performance ◽  
Cutting Tool ◽  
Low Loss ◽  
Compression Process ◽  
Lifting Technique ◽  
Components Analysis

This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of these two approaches is more appropriate for cutting tool wear images analysis. Lifting and Principal Components Analysis were applied in original images of a cutting tool for producing a low resolution version, while keeping the more important details of the image. The low-loss image compression quality provided by these techniques was expressed in terms of the compression factor (ρ), the Mean Square Error (MSE) and the Peak Signal-to-Noise Rate (PSNR) provided by the image compression process. The tests were accomplished using the high-performance language for technical computing MATLAB®, and the results shown that the PCA technique presented the best values of PSNR with low compression rates. However, with high values of compression rates the lifting technique gave the highest PSNR.

scholarly journals Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures

Exacta ◽  
2010 ◽  
Vol 8 (2) ◽  
pp. 225-235
Author(s):  
Fábio Henrique Pereira ◽  
Elesandro Antonio Baptista ◽  
Nivaldo Lemos Coppini ◽  
Rafael Do Espírito-Santo ◽  
Ademir João de Oliveira
Keyword(s):  
Image Compression ◽  
Comparative Study ◽  
Principal Components Analysis ◽  
Principal Components ◽  
High Performance ◽  
Cutting Tool ◽  
Low Loss ◽  
Compression Process ◽  
Lifting Technique ◽  
Components Analysis

This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of these two approaches is more appropriate for cutting tool wear images analysis. Lifting and Principal Components Analysis were applied in original images of a cutting tool for producing a low resolution version, while keeping the more important details of the image. The low-loss image compression quality provided by these techniques was expressed in terms of the compression factor (ρ), the Mean Square Error (MSE) and the Peak Signal-to-Noise Rate (PSNR) provided by the image compression process. The tests were accomplished using the high-performance language for technical computing MATLAB®, and the results shown that the PCA technique presented the best values of PSNR with low compression rates. However, with high values of compression rates the lifting technique gave the highest PSNR.

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