Academic Journal
Application of DCT Compression on Images in IoT Systems.
| Τίτλος: | Application of DCT Compression on Images in IoT Systems. |
|---|---|
| Συγγραφείς: | Jeftenić, Nevena, Rašić, Tamara |
| Πηγή: | International Journal of Electrical Engineering & Computing; Jun2026, Vol. 10 Issue 1, p54-60, 7p |
| Θεματικοί όροι: | Discrete cosine transforms, Image processing, Beekeeping, Machine learning, Internet of things, Data transmission systems, JPEG (Image coding standard) |
| Περίληψη: | Through the integration of sensors, software, and wireless connectivity into everyday activities, the Internet of Things (IoT) creates intelligent ecosystems whose applications are inevitably permeating all segments of life, including smart cities, agriculture, healthcare, and manufacturing. Such systems frequently utilize image and video data as information sources for machine learning and analysis, which are essential for anomaly detection, security surveillance, facial recognition, traffic optimization, and--in the case of this study--monitoring bee activity within a beehive. Given that digital images contain vast amounts of data transmitted through digital processing systems, it is vital to efficiently address the challenges of data transmission within resource-constrained IoT networks. The primary objective of the research presented in this paper is to demonstrate that the application of DCT (Discrete Cosine Transform) compression on images can significantly reduce data volume while simultaneously preserving the image quality required for further application. To evaluate the compression, DCT was applied to JPEG images obtained from smart beekeeping system cameras, utilizing the Python programming language with OpenCV and NumPy libraries. The images were sourced from publicly available datasets. The analysis involved applying DCT compression across six defined quality levels: 1, 5, 20, 50, 80, and 100, covering a range that allows for the assessment of the trade-off between compression ratio and image quality. As expected, the lowest quality factor yields the smallest file sizes but results in the lowest image quality. However, it is significant that even with a moderate factor of 20, substantial optimization is achieved -- a fivefold reduction in data while maintaining satisfactory image quality for further processing. The optimal result is achieved at a factor of 50, which provides a twofold reduction in data and an output image where quality differences, compared to the original, are indiscernible to the naked eye. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Electrical Engineering & Computing is the property of University of East Sarajevo and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edb DbLabel: Complementary Index An: 195601767 RelevancyScore: 1061 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1060.76538085938 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Application of DCT Compression on Images in IoT Systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jeftenić%2C+Nevena%22">Jeftenić, Nevena</searchLink><br /><searchLink fieldCode="AR" term="%22Rašić%2C+Tamara%22">Rašić, Tamara</searchLink> – Name: TitleSource Label: Source Group: Src Data: International Journal of Electrical Engineering & Computing; Jun2026, Vol. 10 Issue 1, p54-60, 7p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Discrete+cosine+transforms%22">Discrete cosine transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Beekeeping%22">Beekeeping</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Data+transmission+systems%22">Data transmission systems</searchLink><br /><searchLink fieldCode="DE" term="%22JPEG+%28Image+coding+standard%29%22">JPEG (Image coding standard)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Through the integration of sensors, software, and wireless connectivity into everyday activities, the Internet of Things (IoT) creates intelligent ecosystems whose applications are inevitably permeating all segments of life, including smart cities, agriculture, healthcare, and manufacturing. Such systems frequently utilize image and video data as information sources for machine learning and analysis, which are essential for anomaly detection, security surveillance, facial recognition, traffic optimization, and--in the case of this study--monitoring bee activity within a beehive. Given that digital images contain vast amounts of data transmitted through digital processing systems, it is vital to efficiently address the challenges of data transmission within resource-constrained IoT networks. The primary objective of the research presented in this paper is to demonstrate that the application of DCT (Discrete Cosine Transform) compression on images can significantly reduce data volume while simultaneously preserving the image quality required for further application. To evaluate the compression, DCT was applied to JPEG images obtained from smart beekeeping system cameras, utilizing the Python programming language with OpenCV and NumPy libraries. The images were sourced from publicly available datasets. The analysis involved applying DCT compression across six defined quality levels: 1, 5, 20, 50, 80, and 100, covering a range that allows for the assessment of the trade-off between compression ratio and image quality. As expected, the lowest quality factor yields the smallest file sizes but results in the lowest image quality. However, it is significant that even with a moderate factor of 20, substantial optimization is achieved -- a fivefold reduction in data while maintaining satisfactory image quality for further processing. The optimal result is achieved at a factor of 50, which provides a twofold reduction in data and an output image where quality differences, compared to the original, are indiscernible to the naked eye. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of International Journal of Electrical Engineering & Computing is the property of University of East Sarajevo and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=195601767 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.7251/IJEEC2601054J Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 54 Subjects: – SubjectFull: Discrete cosine transforms Type: general – SubjectFull: Image processing Type: general – SubjectFull: Beekeeping Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Data transmission systems Type: general – SubjectFull: JPEG (Image coding standard) Type: general Titles: – TitleFull: Application of DCT Compression on Images in IoT Systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jeftenić, Nevena – PersonEntity: Name: NameFull: Rašić, Tamara IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 30293413 Numbering: – Type: volume Value: 10 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Electrical Engineering & Computing Type: main |
| ResultId | 1 |