Critical Analysis of Image Processing Based Classical Approach for Camouflaged Target Detection: Computer Vision Approach

Camouflage is a type of adaptive coloring in which the target blend into its environment making it harder for the predators to see it. It can be accomplished by color matching, disruptive patterns or a combination of the two. Detecting camouflaged targets by naked eyes can be a difficult task or qui...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2023 International Conference on Electrical, Electronics, Communication and Computers (ELEXCOM) s. 1 - 5
Hlavní autoři: Singh, Abhinendra, Bansal, Rishika, Aggarwal, Aarush, Ghosh, Priyodarshi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 26.08.2023
Témata:
Aerospace electronics
color space model
Computational modeling
Computer vision
Image color analysis
Image Fusion
Object detection
OTSU thresholding
Pixel-based image fusion
Thresholding (Imaging)
Wildlife
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Camouflage is a type of adaptive coloring in which the target blend into its environment making it harder for the predators to see it. It can be accomplished by color matching, disruptive patterns or a combination of the two. Detecting camouflaged targets by naked eyes can be a difficult task or quite impossible as the target foreground and the background have undistinguished patterns and colors. So, a Computer Vision technique is required to examine the content of the images and also a technique that is able to distinguish foreground with the background. This paper aims to provide a comparative study on Camouflaged Object Detection (COD) using various classical computer vision approaches which includes Thresholding, Color Space Model and Image Fusion techniques. The comparative and experimental analysis provides an insight of the classical approaches which can be further used for the computer vision applications.
DOI:10.1109/ELEXCOM58812.2023.10370369