An FPGA based co-processor for GLCM texture features measurement

Muhammad  tahir; Ali Roula; A. Bouridane; Fatih  Kurugollu

doi:10.1109/ICECS.2003.1301679

An FPGA based co-processor for GLCM texture features measurement

Muhammad tahir, Ali Roula, A. Bouridane, Fatih Kurugollu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Gray Level Co-occurrence Matrix (GLCM), one of the best known texture analysis methods, estimates image properties related to second-order statistics. These image properties commonly known as texture features can be used for image classification, image segmentation, and remote sensing applications. In this paper, we present an FPGA based co-processor to accelerate the extraction of texture features from GLCM. Handel-C, a recently developed C-like programming language for hardware design, has been used for the FPGA implementation of GLCM texture features measurement. Results show that the FPGA has better speed performances when compared to a general purpose processor for the extraction of GLCM features.

Original language	English
Title of host publication	IEEE Proceedings of IC Electronics, Circuits and Systems
Subtitle of host publication	10th IEEE International Conference on Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003
DOIs	https://doi.org/10.1109/ICECS.2003.1301679
Publication status	Published - 2003

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10.1109/ICECS.2003.1301679

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@inproceedings{3d552cdea36e43c8abd5b3bcf5c05287,

title = "An FPGA based co-processor for GLCM texture features measurement",

abstract = "Gray Level Co-occurrence Matrix (GLCM), one of the best known texture analysis methods, estimates image properties related to second-order statistics. These image properties commonly known as texture features can be used for image classification, image segmentation, and remote sensing applications. In this paper, we present an FPGA based co-processor to accelerate the extraction of texture features from GLCM. Handel-C, a recently developed C-like programming language for hardware design, has been used for the FPGA implementation of GLCM texture features measurement. Results show that the FPGA has better speed performances when compared to a general purpose processor for the extraction of GLCM features.",

author = "Muhammad tahir and Ali Roula and A. Bouridane and Fatih Kurugollu",

year = "2003",

doi = "10.1109/ICECS.2003.1301679",

language = "English",

isbn = "0-7803-8163-7",

booktitle = "IEEE Proceedings of IC Electronics, Circuits and Systems",

}

An FPGA based co-processor for GLCM texture features measurement. / tahir, Muhammad ; Roula, Ali; Bouridane, A. et al.
IEEE Proceedings of IC Electronics, Circuits and Systems: 10th IEEE International Conference on Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003. 2003.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An FPGA based co-processor for GLCM texture features measurement

AU - tahir, Muhammad

AU - Roula, Ali

AU - Bouridane, A.

AU - Kurugollu, Fatih

PY - 2003

Y1 - 2003

N2 - Gray Level Co-occurrence Matrix (GLCM), one of the best known texture analysis methods, estimates image properties related to second-order statistics. These image properties commonly known as texture features can be used for image classification, image segmentation, and remote sensing applications. In this paper, we present an FPGA based co-processor to accelerate the extraction of texture features from GLCM. Handel-C, a recently developed C-like programming language for hardware design, has been used for the FPGA implementation of GLCM texture features measurement. Results show that the FPGA has better speed performances when compared to a general purpose processor for the extraction of GLCM features.

AB - Gray Level Co-occurrence Matrix (GLCM), one of the best known texture analysis methods, estimates image properties related to second-order statistics. These image properties commonly known as texture features can be used for image classification, image segmentation, and remote sensing applications. In this paper, we present an FPGA based co-processor to accelerate the extraction of texture features from GLCM. Handel-C, a recently developed C-like programming language for hardware design, has been used for the FPGA implementation of GLCM texture features measurement. Results show that the FPGA has better speed performances when compared to a general purpose processor for the extraction of GLCM features.

U2 - 10.1109/ICECS.2003.1301679

DO - 10.1109/ICECS.2003.1301679

M3 - Conference contribution

SN - 0-7803-8163-7

BT - IEEE Proceedings of IC Electronics, Circuits and Systems

ER -

An FPGA based co-processor for GLCM texture features measurement

Abstract

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