基于离散小波变换的车辆跟踪系统

Sudheer Babu Punuri
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引用次数: 0

摘要

考虑到速度在互联网领域的重要性和大量的网络攻击,需要快速、准确、方便的验证系统。虽然可以操纵图像识别验证,但它仍然可以帮助防止任何形式的欺诈方案。本研究提出了一种用于识别定位点的逐像素操作模型。计算机视觉并不局限于像素操作。它可能比图像处理更复杂。首先,采用k均值聚类算法对非结构化图像进行分割;然后,在完成预处理步骤后,从监控摄像机中提取分割后的图像,用于识别表情和车辆图像。监控摄像机的原始图像包括通过DWT进行分类的个人和车辆图像。此外,代表外观的图像是由智能自拍点击(SSC)拍摄的。提取这两个特征是为了确定车辆是否应该被允许进入校园,从而使验证成为可能。这两幅图像都是提取出来的可靠物体,用于位置识别。
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Vehicle Tracking System Using Discrete Wavelet Transformation
Given the significance of speed in the realm of the Internet and the large number of cyberattacks, verification systems that are fast, accurate, and convenient are required. Although it is possible to manipulate Image Recognition verification, it can still be of some help against any form of fraudulent scheme. The present study proposes a model of pixel-wise operations for identifying a location point. The computer vision is not limited to pixel-wise operations. It can be more complicated than image processing. First, unstructured image segmentation is taken via K-Means Clustering Algorithm. Then, after completing the preprocessing step, the segmented image is extracted from the surveillance cameras to identify expressions and vehicle images. Raw images of the surveillance camera comprise the images of individuals and vehicles that are classified by means of DWT. Further, the images that represent the appearances are taken by Smart Selfie Click (SSC). These two features are extracted in order to identify whether or not a vehicle should be permitted into the campus, thus making the verification possible. These two images are nothing but reliable objects extracted and used for location identification.
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来源期刊
International Journal of Industrial Engineering and Production Research
International Journal of Industrial Engineering and Production Research Engineering-Industrial and Manufacturing Engineering
CiteScore
1.60
自引率
0.00%
发文量
0
审稿时长
10 weeks
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