Table 1: Comparative analysis of existing Modified/Improved SIFT techniques.

MethodDescriptionRecognition rate on JAFFE databaseRemarks
Total imagesRecognized imagesRecognition rate

Tang et al. [13]
(modified SIFT with EMD)
The algorithm has been implemented to recognize the objects under noise.21316276.05%Approach is suitable for recognition of objects taken under different view points [13] but does not recognize the facial expressions properly.

Bastanlar et al. [14]
(improved SIFT matching)
The algorithm has been performed on pair of 30 images, viewing four different scenes (indoor and outdoor). 21315773.70%In this method, scale problem of image is eliminated and approach is significant for wide-baseline perspective images pairs and hybrid camera pairs [14].

Ke and Sukthankar [15]
The matching performance of the algorithm has been evaluated on Graffiti 6 dataset.21316175.58%Approach is suitable for yielding concise interesting points, which are invariant over transformations on images caused by changes in camera pose and lightning [15].

Abdul-Jabbar et al. [16] (APCAWT + SIFT)It was implemented on 200 images of AT&T ORL database and proposed denoised database with accuracy ratio of 85% and 86%, respectively.21316878.87%It performs well for recognition of face images [16], but it does not yield good result when implemented on JAFFEE database to compare different expressions of face image with only face images of neutral expression (to reduce the database).