This paper presents the performance comparison of feature matching algorithms SIFT (scale invariant feature transform) and ISIFT (Iterative scale invariant feature transform). In SIFT, invariant feature key points of an images are extracted to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation. In ISIFT for accurate matching of images, the relative view and illumination between the images estimated iteratively. The

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... hing performance not effected by view and illumination changes in a threshold ranges. The threshold values reflects the maximum allowable change in view and illumination between the images. After comparison of SIFT and ISIFT matching algorithms, the results shows that the ISIFT algorithm consists of accurate matching rate and scale invariant to illumination change.