In real world applications, tracking target in low resolution video is a challenging task because there is loss of discriminative detail in the visual appearance of moving object. The existing methods are mostly based on the enhancement of LR (low resolution) video by super resolution techniques. But these methods require high computational cost. This cost further increases if we are dealing with events detection. In this paper we present an algorithm which is able to detect unusual events without such type of conversion and well suited for enhancement of security of ATMs where conventional low resolution cameras are generally used due to their low cost. Proposed algorithm only uses close morphological operation with disk like structuring element in the preprocessing steps to cope up with low resolution video. It further uses rolling average background subtraction technique to detect foreground object from dynamic background in a scene. Our proposed algorithm is able to recognize the occurrence of uncommon events such as overcrowding or fight in the low resolution video simply by using statistical property, standard deviation of moving objects. It is fast enough because it process low resolution frames and could be helpful in surveillance system for enhancing the security of ATMs where conventional camera of low resolution are still used. It does not use any classifier and avoids the requirement of training the system initially.
In Steganography there are many techniques which are used to hide the data in different formats. Most general one is the least significant bit (LSB) substitution method, which is commonly used due to its simplicity. It provides protection to data by hiding it in digital image. But simple use of this approach is more vulnerable to attack. In this paper we have discussed the art and science of Steganography in general and proposed an algorithm which is the variant of LSB substitution method. It efficiently and effectively hides data with the help of a key in JPEG colored digital image. Security of hidden data is proportional to the length of key used. Proposed algorithm is capable to hide more data in cover image and require no pre processing. Results show that there is less detectable distortion in the stego image and opens the track for proposed algorithm to be used in data hiding and secure transmission.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.