TY - JOUR
T1 - Implementation of a parallel algorithm of image segmentation based on region growing
AU - Álvarez-Cedillo, Jesús Antonio
AU - Aguilar-Fernández, Mario
AU - Álvarez-Sánchez, Teodoro
AU - Sandoval-Gómez, Raúl Junior
N1 - Funding Information:
We appreciate the facilities granted to carry out this work to the INSTITUTO POLITECNICO NACIONAL through the Secretary of Research and Postgraduate with the SIP project 20180023. To the Interdisciplinary Unit of Engineering and Social and Administrative Sciences, Center for Research and Development of Digital Technology. Likewise, the Program for Stimulating the Performance of Researchers (EDI) and the Program for Stimulating Teaching Performance. (EDD) and COFAA.
PY - 2020
Y1 - 2020
N2 - In computer vision and image processing, image segmentation remains a relevant research area that contains many partially answered research questions. One of the fields of most significant interest in Digital Image Processing corresponds to segmentation, a process that breaks down an image into its different components that make it up. A technique widely used in the literature is called Region Growing, this technique makes the identification of textures, through the use of characteristic and particular vectors. However, the level of its computational complexity is high. The traditional methods of Region growing are based on the comparison of grey levels of neighbouring pixels, and usually, fail when the region to be segmented contains intensities similar to adjacent regions. However, if a broad tolerance is indicated in its thresholds, the detected limits will exceed the region to identify; on the contrary, if the threshold tolerance decreases too much, the identified region will be less than the desired one. In the analysis of textures, multiple scenes can be seen as the composition of different textures. The visual texture refers to the impression of roughness or smoothness that some surfaces created by the variations of tones or repetition of visual patterns therein. The texture analysis techniques are based on the assignment of one or several parameters indicating the characteristics of the texture present to each region of the image. This paper shows how a parallel algorithm was implemented to solve open problems in the area of image segmentation research. Region growing is an advanced approach to image segmentation in which neighbouring pixels are examined one by one and added to an appropriate region class if no border is detected. This process is iterative for each pixel within the boundary of the region. If adjacent regions are found, a region fusion algorithm is used in which weak edges dissolve, and firm edges remain intact, this requires a lot of processing time on a computer to make parallel implementation possible
AB - In computer vision and image processing, image segmentation remains a relevant research area that contains many partially answered research questions. One of the fields of most significant interest in Digital Image Processing corresponds to segmentation, a process that breaks down an image into its different components that make it up. A technique widely used in the literature is called Region Growing, this technique makes the identification of textures, through the use of characteristic and particular vectors. However, the level of its computational complexity is high. The traditional methods of Region growing are based on the comparison of grey levels of neighbouring pixels, and usually, fail when the region to be segmented contains intensities similar to adjacent regions. However, if a broad tolerance is indicated in its thresholds, the detected limits will exceed the region to identify; on the contrary, if the threshold tolerance decreases too much, the identified region will be less than the desired one. In the analysis of textures, multiple scenes can be seen as the composition of different textures. The visual texture refers to the impression of roughness or smoothness that some surfaces created by the variations of tones or repetition of visual patterns therein. The texture analysis techniques are based on the assignment of one or several parameters indicating the characteristics of the texture present to each region of the image. This paper shows how a parallel algorithm was implemented to solve open problems in the area of image segmentation research. Region growing is an advanced approach to image segmentation in which neighbouring pixels are examined one by one and added to an appropriate region class if no border is detected. This process is iterative for each pixel within the boundary of the region. If adjacent regions are found, a region fusion algorithm is used in which weak edges dissolve, and firm edges remain intact, this requires a lot of processing time on a computer to make parallel implementation possible
KW - Digital Image Processing
KW - GPU
KW - Region growing
KW - SIMD
KW - computer vision
KW - image processing
KW - parallel algorithms
KW - parallel processing
KW - segmentation techniques
KW - texture analysis
UR - http://www.scopus.com/inward/record.url?scp=85086935871&partnerID=8YFLogxK
U2 - 10.15587/1729-4061.2020.197095
DO - 10.15587/1729-4061.2020.197095
M3 - Artículo
AN - SCOPUS:85086935871
SN - 1729-3774
VL - 1
SP - 6
EP - 11
JO - Eastern-European Journal of Enterprise Technologies
JF - Eastern-European Journal of Enterprise Technologies
IS - 9-103
ER -