Motion detect application with frame difference method on a surveillance camera

Abstract

Security becomes one of the major necessities in our lives nowadays however criminal activities are still at large with criminals unable to be persecuted without eligible proofs of their misdeeds. Surveillance Camera is one of the better solutions to these problems in which they can be positioned at every corner of a building even streets and alleys. Their functions can be enhanced by adding algorithms that can identify objects. Frame Differences method is an algorithm to identify an object’s motion. Using this algorithm, we could differentiate an object moving in the environment. Background subtraction is one of the methods suitable to further improve frame differences thus increasing its effectiveness and precision. After implementing the method on a camera, the luminosity was founded to influence the threshold value significantly, the threshold value of 35 is the optimal value.

Early and Objective Evaluation of the Therapeutic Effects of ADHD Medication through Movement Analysis Using Video Recording Pixel Subtraction

“…We thus introduce the pixel subtraction method, a new objective approach for assessing the ADHD treatment response, which can serve as an adjuvant to the SNAP questionnaire. Devi et al mentioned that the frame subtraction method is an efficient alternativ comparing image pixel values in subsequent frames captured 2 s apart, with the frame serving as reference and the second frame containing the moving object; the frames (images) are compared to detect movement by calculating the differences in p values [7,9]. Increased activity is characteristic of patients with ADHD; thus, movem analysis can be a useful technique [10,11].…”

“…Image processing has attracted interest in video surveillance applications [ 6 ], especially for understanding human activity [ 7 ]. Movement detection involves tracking moving objects by using an algorithm [ 6 ].…”

“…This conversion decreased the operational calculation time without affecting the result of the movement analysis. Thus, it is used in various circumstances for movement detection [ 7 ]. However, this technique has been underutilized in the medical field.…”

Identification and Classification of Crowd Activities

“…So, analyzing individual behavior in crowded scenes is one of the most important and challenging areas in current research. The main steps of our framework: Firstly, we start with identifying the crowd and use object detection techniques to analyze crowds at microscopic levels [8]. Individuals in a crowd can move in the same direction or randomly.…”

Enhancing the Quality of Cellular Camera Video With Convolutional Neural Network

“…The development of research in the field of computer vision in recent years has shown sophisticated performance with a high degree of accuracy due to the application in various fields such as face recognition - (Wijaya, Husein, & Harahap, 2017), signature identification (Harahap, Husein, & Dharma, 2017) - and camera surveillance (Husein, Calvin, Raymond, & William, 2018), recently the application of convolutional neural networks, for example object detection - (Wijaya, Husein, & Harahap, 2017), (Harahap, Husein, & Dharma, 2017) - , (Husein, Calvin, Raymond, & William, 2018) - (Jeong, Park, & kwak, 2017) - (Zhang, Wen, Bian, Lei, & Z, 2018), and (Ren, He, Girshick, & Sun, 2015) - (Ahn, Kang, & Sohn, 2019), pedestrians (Haris, Shakhnarovich, & Ukita, 2019), (Caballero, et al, 2017). Recent image restorations such as super resolution (Kim, Lim, Na, & Kim, 2018) - (Shi, et al, 2016), (Ignatov, Kobyshev, Timofte, Vanhoey, & Gool, 2018) and super resolution video (Vorobjov, Zakharava, Bohush, & Ablameyko, 2018), experienced a significant increase thanks to deep learning with the aim of helping produce visual video applications.…”