Optimized Multi-layer Machine Learning Technique for Movement Detection and Tracking in Video Data Stream
Manisha Devi1, Nidhi Bhatla2, Harinder Kaur3
1Manisha Devi, M.tech student at Department of CSE, Sachdeva Engineering College for girls , Gharuan(Mohali), Punjab,India.
2Er. Nidhi Bhatla, HOD (CSE) at Sachdeva Engineering College for Girls, Gharuan(Mohali), Punjab, India.
3Er. Harinder Kaur, Assistant Professor at Sachdeva Engineering College for Girls, Gharuan(Mohali), Punjab, India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 07 July 2019 | Manuscript published on 30 August 2019 | PP: 1151-1159 | Volume-8 Issue-10, August 2019 | Retrieval Number: J91310881019/2019©BEIESP | DOI: 10.35940/ijitee.J9131.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the advent in technology, security and authentication has become the main aspect in computer vision approach. Moving object detection is an efficient system with the goal of preserving the perceptible and principal source in a group. Surveillance is one of the most crucial requirements and carried out to monitor various kinds of activities. The detection and tracking of moving objects are the fundamental concept that comes under the surveillance systems. Moving object recognition is challenging approach in the field of digital image processing. Moving object detection relies on few of the applications which are Human Machine Interaction (HMI), Safety and video Surveillance, Augmented Realism, Transportation Monitoring on Roads, Medical Imaging etc. The main goal of this research is the detection and tracking moving object. In proposed approach, based on the pre-processing method in which there is extraction of the frames with reduction of dimension. It applies the morphological methods to clean the foreground image in the moving objects and texture based feature extract using component analysis method. After that, design a novel method which is optimized multilayer perceptron neural network. It used the optimized layers based on the Pbest and Gbest particle position in the objects. It finds the fitness values which is binary values (x_update, y_update) of swarm or object positions. Method and output achieved final frame creation of the moving objects in the video using BLOB ANALYSER In this research , an application is designed using MATLAB VERSION 2016a In activation function to re-filter the given input and final output calculated with the help of pre-defined sigmoid. In proposed methods to find the clear detection and tracking in the given dataset MOT, FOOTBALL, INDOOR and OUTDOOR datasets. To improve the detection accuracy rate, recall rate and reduce the error rates, False Positive and Negative rate and compare with the various classifiers such as KNN, MLPNN and J48 decision Tree.
Keywords: Digital image processing, Human Machine Interaction, Moving object recognition, Authentication.
Scope of the Article: Machine Learning