Idle Object Detection in Video for Banking ATM Applications

Abstract: This study proposes a method to detect idle object and applies it for analysis of suspicious events. Partitioning and Normalized Cross Correlation (PNCC) based algorithm is proposed for the detection of moving object. This algorithm takes less processing time, which increases the speed and also the detection rate. In this an approach is proposed for the detection and tracking of moving object in an image sequence. Two consecutive frames from image sequence are partitioned into four quadrants and then the Normalized Cross Correlation (NCC) is applied to each sub frame. The sub frame which has minimum value of NCC, indicates the presence of moving object. The proposed system is going to use the suspicious tracking of human behaviour in video surveillance and it is mainly used for security purpose in ATM application. The suspicious object's visual properties so that it can be accurately segmented from videos. After analyzing its subsequent motion features, different abnormal events like robbery can be effectively detected from videos. The suspicious action in ATM are many, such as using mobile phones, multiple persons trying to access the ATM machine in same time, kicking of each other, idle object and it shows event corresponding to Vandalism and robbery. In proposed system, idle object detection is used to identify by using PNCC algorithm with P-filter (Particle) and by extracting the features of the object in an enhanced way by using the curvelet based transformation

An efficient character segmentation based on VNP algorithm

Abstract: Character segmentation is an important preprocessing stage in image processing applications such as OCR, License Plate Recognition, electronic processing of checks in banks, form processing and, label and barcode recognition. It is essential to have an efficient character segmentation technique because it affects the performance of all the processes that follow and hence, the overall system accuracy. Vertical projection profile is the most common segmentation technique. However, the segmentation results are not always correct in cases where pixels of adjacent characters fall on the same scan line and a minimum threshold is not observed in the histogram to segment the respective adjacent characters. In this study, a character segmentation technique based on Visited Neighbor Pixel (VNP) Algorithm is proposed, which is an improvement to the vertical projection profile technique. VNP Algorithm performs segmentation based on the connectedness of the pixels on the scan line with that of the previously visited pixels. Therefore, a clear line of separation is found even when the threshold between two adjacent characters is not minimal. The segmentation results of the traditional vertical projection profile and the proposed method are compared with respect to a few selected fonts and the latter, with an average accuracy of approximately 94%, has shown encouraging results

Managing Cyber Threats in the Age of Technology

This chapter highlights the importance of risk detection and cybersecurity in modern computing systems. As technology continues to advance, these components become increasingly critical for ensuring the successful operation of these systems. The chapter suggests that failure to properly address these issues can result in serious consequences, including the compromise of sensitive information and the disruption of critical systems. Therefore, it is essential for organizations to prioritize risk detection and cybersecurity as a foundational element of their computing infrastructure

Managing cyber threats in the age of technology: The role of risk detection and cyber security

This chapter highlights the importance of risk detection and cybersecurity in modern computing systems. As technology continues to advance, these components become increasingly critical for ensuring the successful operation of these systems. The chapter suggests that failure to properly address these issues can result in serious consequences, including the compromise of sensitive information and the disruption of critical systems. Therefore, it is essential for organizations to prioritize risk detection and cybersecurity as a foundational element of their computing infrastructure

Securing the Future

Risk detection and cybersecurity are critical components for the success of contemporary computing systems. With the increasing reliance on technology and the Internet, cyber threats have become more complex and sophisticated, posing a significant challenge to the security of computer systems. In this chapter, the authors examine the importance of risk detection and cybersecurity measures in contemporary computing, highlighting the potential risks and threats that can impact system performance and integrity. They explore various techniques and tools used in risk detection and cybersecurity, including intrusion detection systems, firewalls, and encryption methods. Additionally, the authors discuss the role of risk management in identifying and mitigating potential threats to computing systems. They conclude that risk detection and cybersecurity measures are essential for the successful operation of contemporary computing systems and highlight the need for continued investment and innovation in this critical area