SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON
Video surveillance technology, such as CCTV, is increasingly common in various applications, including public safety and business surveillance. Analyzing and comparing images from CCTV systems is essential for ensuring safety and security. This research implements the Pearson Correlation method in P...
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| Format: | Article |
| Language: | English |
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Universitas Pattimura
2024-10-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/13549 |
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| author | Angga Dwi Mulyanto Bambang Widjanarko Otok Hasri Wiji Aqsari Sri Harini Cindy Cahyaning Astuti |
| author_facet | Angga Dwi Mulyanto Bambang Widjanarko Otok Hasri Wiji Aqsari Sri Harini Cindy Cahyaning Astuti |
| author_sort | Angga Dwi Mulyanto |
| collection | DOAJ |
| description | Video surveillance technology, such as CCTV, is increasingly common in various applications, including public safety and business surveillance. Analyzing and comparing images from CCTV systems is essential for ensuring safety and security. This research implements the Pearson Correlation method in Python to measure the similarity of CCTV images. Pearson Correlation, which assesses the linear relationship between two variables, is employed to compare the pixel values of two images, resulting in a coefficient that indicates the degree of similarity. We used a quantitative approach with experiments on two scenarios to test the program's effectiveness in measuring image similarity. The results demonstrate that Pearson Correlation is highly effective in distinguishing between identical and other images, providing a more accurate and comprehensive assessment of image similarity compared to histogram analysis. However, the findings are constrained by the specific scenarios and dataset utilized. Further research with more diverse empirical data is required to generalize these results across a broader range of CCTV conditions. |
| format | Article |
| id | doaj-art-7ecf3e371ba14600a96fa29a2dfdebe7 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-7ecf3e371ba14600a96fa29a2dfdebe72025-08-20T03:37:34ZengUniversitas PattimuraBarekeng1978-72272615-30172024-10-011842703271210.30598/barekengvol18iss4pp2703-271213549SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHONAngga Dwi Mulyanto0Bambang Widjanarko Otok1Hasri Wiji Aqsari2Sri Harini3Cindy Cahyaning Astuti4Departement of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, IndonesiaDepartement of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, IndonesiaDepartement of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, IndonesiaMathematics Study Program, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim Malang, IndonesiaInformation Technology Education Study Program, Faculty of Psychology and Education, Universitas Muhammadiyah Sidoarjo, IndonesiaVideo surveillance technology, such as CCTV, is increasingly common in various applications, including public safety and business surveillance. Analyzing and comparing images from CCTV systems is essential for ensuring safety and security. This research implements the Pearson Correlation method in Python to measure the similarity of CCTV images. Pearson Correlation, which assesses the linear relationship between two variables, is employed to compare the pixel values of two images, resulting in a coefficient that indicates the degree of similarity. We used a quantitative approach with experiments on two scenarios to test the program's effectiveness in measuring image similarity. The results demonstrate that Pearson Correlation is highly effective in distinguishing between identical and other images, providing a more accurate and comprehensive assessment of image similarity compared to histogram analysis. However, the findings are constrained by the specific scenarios and dataset utilized. Further research with more diverse empirical data is required to generalize these results across a broader range of CCTV conditions.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/13549pearson correlationimage similaritypython |
| spellingShingle | Angga Dwi Mulyanto Bambang Widjanarko Otok Hasri Wiji Aqsari Sri Harini Cindy Cahyaning Astuti SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON Barekeng pearson correlation image similarity python |
| title | SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON |
| title_full | SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON |
| title_fullStr | SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON |
| title_full_unstemmed | SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON |
| title_short | SIMILARITY CHECKING OF CCTV IMAGES USING PEARSON CORRELATION: IMPLEMENTATION WITH PYTHON |
| title_sort | similarity checking of cctv images using pearson correlation implementation with python |
| topic | pearson correlation image similarity python |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/13549 |
| work_keys_str_mv | AT anggadwimulyanto similaritycheckingofcctvimagesusingpearsoncorrelationimplementationwithpython AT bambangwidjanarkootok similaritycheckingofcctvimagesusingpearsoncorrelationimplementationwithpython AT hasriwijiaqsari similaritycheckingofcctvimagesusingpearsoncorrelationimplementationwithpython AT sriharini similaritycheckingofcctvimagesusingpearsoncorrelationimplementationwithpython AT cindycahyaningastuti similaritycheckingofcctvimagesusingpearsoncorrelationimplementationwithpython |