Performance Enhancement of Image Stitching Process Under Bound Energy aided feature matching and Varying Illumination Environments

International Journal of Electronics and Communication Engineering

© 2019 by SSRG - IJECE Journal

Volume 6 Issue 9

Year of Publication : 2019

Authors : Venkat P. Patil, Dr. C. Ram Singla

10.14445/23488549/IJECE-V6I9P101

How to Cite?

Venkat P. Patil, Dr. C. Ram Singla, "Performance Enhancement of Image Stitching Process Under Bound Energy aided feature matching and Varying Illumination Environments," SSRG International Journal of Electronics and Communication Engineering, vol. 6,  no. 9, pp. 1-6, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I9P101

Abstract:

Stitched images is a method that mixes several images or images of the intersecting perspective field to create a high-resolution panoramic image. In the field of medical imagery, satellite data, computer vision, military automatic target identifiers, we can see the importance of image mosaicing. The fields of computer vision, photography and computer graphics are currently being researched on image stitching and video stitching. Registration of images includes five major steps: detection of image features and its description; matching features; outsider rejection; deriving transformation function; and reproduction of images. Stitching images of similar images is a difficult job when images are captured in variable light conditions. In this paper, we have examined image panorama development which is based on seamless image stitching to overcome the above mentioned problems by adopting the de-hazing technique on the acquired wide view scenes. This is achieved further before identifying the image functionalities and bound energy-energized features that match the image's invariant scale attributes (SIFT). Compared to the current image stitching techniques the experimentation of the suggested model uses squared distance to match the features. The suggested seamless stitchable technique is assessed on the basis of metrics VSGV and HSGV called as “Vertical Square Gradient Value” and “Horizontal Square Gradient Value” and respectively. Analysis of the aforementioned stitching algorithm aims at reducing the amount of computation time and inconsistencies in the stitched result obtained.

Keywords:

Bound Energy, ASIFT, FAST, FREAK, Panorama.

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