Crowd level estimation based on head detection
| dc.contributor.author | Loh Kah Leong | |
| dc.date.accessioned | 2021-02-23T02:21:07Z | |
| dc.date.available | 2021-02-23T02:21:07Z | |
| dc.date.issued | 2019-06 | |
| dc.description.abstract | Image processing is one of the most common terms in vision technology. In general, it can be clustered into a few groups: checking for presence, object detection and localization, measurement, identification and verification. In image processing operation, the given input image is the input and the output is the high quality or more information picture depend on technique used. Human detection is one of the most important part in image processing. A computer system can be trained by different algorithm and after checking the input image can identify the number and position of human in the input picture. Image processing is a time consuming process, in this project our study is provides and test the most suitable algorithm used in human detection which provide less processing time and highest accuracy in human detection. In the image processing part Viola Jones Algorithm is the best option for object detection image processing. Haar cascade classifier window are able to detect all the coordinates in the picture with different scale about the possible of human head in the input image. Viola Jones Algorithm is ran using MATLAB to test and obtain the best performance which using the shortest execute time to get the most accuracy result. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/11451 | |
| dc.language.iso | en | en_US |
| dc.title | Crowd level estimation based on head detection | en_US |
| dc.type | Other | en_US |
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