Detection of grains in aluminium metal matrix composites using image fusion
Abstract Aluminium metal matrix composites are lightweight, corrosion-resistant, and extremely durable. Because of their low mass density, stiffness, and high specific strength, aluminium alloys with ceramic-reinforced particles are more appealing in aircraft, transportation, and industrial applicat...
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| Format: | Article |
| Language: | English |
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Springer
2025-06-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-025-07197-6 |
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| author | Tapasmini Sahoo Sweta Rani Biswal Kunal Kumar Das |
| author_facet | Tapasmini Sahoo Sweta Rani Biswal Kunal Kumar Das |
| author_sort | Tapasmini Sahoo |
| collection | DOAJ |
| description | Abstract Aluminium metal matrix composites are lightweight, corrosion-resistant, and extremely durable. Because of their low mass density, stiffness, and high specific strength, aluminium alloys with ceramic-reinforced particles are more appealing in aircraft, transportation, and industrial applications. This piece of work illustrates an image fusion approach using discrete wavelet transform (DWT) for the detection of grains present in the hybrid composite to study the metallographic characterization. The fusion approach combines the same composite's images with different resolutions and intensities acquired by scanning electron microscope to produce an integrated image that is more suited for identifying grains and grain boundaries that are difficult to locate from images in other modalities. Some statistical evaluation measures are used to investigate the effectiveness and significance of the suggested fusion technique. The statistical measure’s indicate that the recommended methodology is commendable. According to the statistical analysis, the proposed fusion process successfully retains the maximal content of visual truth in material characterization, allowing for faster and more accurate metallographic characterization of hybrid composites. |
| format | Article |
| id | doaj-art-4e3c5c82dfda481da4c25edd5d9862a5 |
| institution | DOAJ |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-4e3c5c82dfda481da4c25edd5d9862a52025-08-20T03:10:35ZengSpringerDiscover Applied Sciences3004-92612025-06-017611210.1007/s42452-025-07197-6Detection of grains in aluminium metal matrix composites using image fusionTapasmini Sahoo0Sweta Rani Biswal1Kunal Kumar Das2Department of Electronics and Communication Engineering, FET, Siksha O Anusandhan (Deemed to Be University)Department of Mechanical Engineering, FET, Siksha O Anusandhan (Deemed to Be University)Department of Electronics and Communication Engineering, FET, Siksha O Anusandhan (Deemed to Be University)Abstract Aluminium metal matrix composites are lightweight, corrosion-resistant, and extremely durable. Because of their low mass density, stiffness, and high specific strength, aluminium alloys with ceramic-reinforced particles are more appealing in aircraft, transportation, and industrial applications. This piece of work illustrates an image fusion approach using discrete wavelet transform (DWT) for the detection of grains present in the hybrid composite to study the metallographic characterization. The fusion approach combines the same composite's images with different resolutions and intensities acquired by scanning electron microscope to produce an integrated image that is more suited for identifying grains and grain boundaries that are difficult to locate from images in other modalities. Some statistical evaluation measures are used to investigate the effectiveness and significance of the suggested fusion technique. The statistical measure’s indicate that the recommended methodology is commendable. According to the statistical analysis, the proposed fusion process successfully retains the maximal content of visual truth in material characterization, allowing for faster and more accurate metallographic characterization of hybrid composites.https://doi.org/10.1007/s42452-025-07197-6Metal matrix compositesCorrosionImage fusionHybrid composites |
| spellingShingle | Tapasmini Sahoo Sweta Rani Biswal Kunal Kumar Das Detection of grains in aluminium metal matrix composites using image fusion Discover Applied Sciences Metal matrix composites Corrosion Image fusion Hybrid composites |
| title | Detection of grains in aluminium metal matrix composites using image fusion |
| title_full | Detection of grains in aluminium metal matrix composites using image fusion |
| title_fullStr | Detection of grains in aluminium metal matrix composites using image fusion |
| title_full_unstemmed | Detection of grains in aluminium metal matrix composites using image fusion |
| title_short | Detection of grains in aluminium metal matrix composites using image fusion |
| title_sort | detection of grains in aluminium metal matrix composites using image fusion |
| topic | Metal matrix composites Corrosion Image fusion Hybrid composites |
| url | https://doi.org/10.1007/s42452-025-07197-6 |
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