TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications
Superpixel segmentation aims to produce a consistent grouping of pixels. In recent years, the importance of superpixel segmentation has increased in computer vision since it offers useful primitives for extracting image features and simplifies the complexity of other image processing steps. In this...
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MDPI AG
2024-12-01
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| author | Abiel Aguilar-González Alejandro Medina Santiago Jorge Antonio Orozco Torres J. A. de Jesús Osuna-Coutiño Madaín Pérez Patricio Néstor A. Morales-Navarro |
| author_facet | Abiel Aguilar-González Alejandro Medina Santiago Jorge Antonio Orozco Torres J. A. de Jesús Osuna-Coutiño Madaín Pérez Patricio Néstor A. Morales-Navarro |
| author_sort | Abiel Aguilar-González |
| collection | DOAJ |
| description | Superpixel segmentation aims to produce a consistent grouping of pixels. In recent years, the importance of superpixel segmentation has increased in computer vision since it offers useful primitives for extracting image features and simplifies the complexity of other image processing steps. In this work, we propose the TurboPixels algorithm, whose main contribution is a hardware architecture for superpixel segmentation. Compared with previous approaches, our superpixels are computed without the need for iterative loops. This makes it possible to reduce algorithmic complexity and increases processing speed. The experimental results indicate that our approach enables a small-scale FPGA-based implementation suitable for embedded applications. In addition, the results demonstrate that robust superpixel segmentation can be achieved with processing speeds up to 86 times faster than in previous works in the current literature. |
| format | Article |
| id | doaj-art-e60c9f53b4374865870249facf64e988 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e60c9f53b4374865870249facf64e9882024-12-27T14:08:45ZengMDPI AGApplied Sciences2076-34172024-12-0114241191210.3390/app142411912TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded ApplicationsAbiel Aguilar-González0Alejandro Medina Santiago1Jorge Antonio Orozco Torres2J. A. de Jesús Osuna-Coutiño3Madaín Pérez Patricio4Néstor A. Morales-Navarro5Computer Science Department, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), San Andrés Cholula 72840, MexicoComputer Science Department, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), San Andrés Cholula 72840, MexicoIndustrial Engineering Department, Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez (ITTG), Tuxtla Gutiérrez 29050, MexicoMechatronics Engineering Department, Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez (ITTG), Tuxtla Gutiérrez 29050, MexicoMechatronics Engineering Department, Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez (ITTG), Tuxtla Gutiérrez 29050, MexicoMechatronics Engineering Department, Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez (ITTG), Tuxtla Gutiérrez 29050, MexicoSuperpixel segmentation aims to produce a consistent grouping of pixels. In recent years, the importance of superpixel segmentation has increased in computer vision since it offers useful primitives for extracting image features and simplifies the complexity of other image processing steps. In this work, we propose the TurboPixels algorithm, whose main contribution is a hardware architecture for superpixel segmentation. Compared with previous approaches, our superpixels are computed without the need for iterative loops. This makes it possible to reduce algorithmic complexity and increases processing speed. The experimental results indicate that our approach enables a small-scale FPGA-based implementation suitable for embedded applications. In addition, the results demonstrate that robust superpixel segmentation can be achieved with processing speeds up to 86 times faster than in previous works in the current literature.https://www.mdpi.com/2076-3417/14/24/11912image processingimage segmentationreal-time processingFPGAVHDL |
| spellingShingle | Abiel Aguilar-González Alejandro Medina Santiago Jorge Antonio Orozco Torres J. A. de Jesús Osuna-Coutiño Madaín Pérez Patricio Néstor A. Morales-Navarro TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications Applied Sciences image processing image segmentation real-time processing FPGA VHDL |
| title | TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications |
| title_full | TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications |
| title_fullStr | TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications |
| title_full_unstemmed | TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications |
| title_short | TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications |
| title_sort | turbopixels a superpixel segmentation algorithm suitable for real time embedded applications |
| topic | image processing image segmentation real-time processing FPGA VHDL |
| url | https://www.mdpi.com/2076-3417/14/24/11912 |
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