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Abstract
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Article Information:
Single Core Hardware Approach to Implement Fuzzy Wavelet Based Textures Segmentation with a Single System Clock
Labonnah F. Rahman, Md. Mamun, H. Husain, Mohd. Marufuzzaman and Yushaizad Yusuf
Corresponding Author: Labonnah Farzana Rahman
Submitted: 2011 October, 15
Accepted: 2011 November, 18
Published: 2012 April, 01 |
Abstract:
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Texture refers to the surface properties that can be easily described by its primitives (tones) and their
spatial relationship. Texture analysis is a process to find the shape, segment or identify the region of interest
on the object. In this research study, we approach to implement unsupervised texture segmentation in hardware.
First, the Discrete Wavelet Transform (DWT) is used to extract the input image and sample it into different
frequency bands. After this process, the input image becomes smaller and compressed. This input image is then
fed into fuzzy K-mean Clustering algorithm. and many computations are needed for the correct segmentation
assignment. Hence, the total execution time for segmentation is improved using compressed image as input.
From the simulation result, images with two to five t Fuzzy K-mean is a well-known and precise supervised
clustering algorithm that divides the image into different segmentations ypes of textures were successfully
detected around 0.025-0.033 sec. The proposed hardware approach for wavelet based texture segmentation is
able to reduce the execution time, to enhance the performance for 128*128 pixels, which can be considered as
fast segmentation solution.
Key words: FPGA, fuzzy, texture segmentation, wavelet, , ,
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Cite this Reference:
Labonnah F. Rahman, Md. Mamun, H. Husain, Mohd. Marufuzzaman and Yushaizad Yusuf, . Single Core Hardware Approach to Implement Fuzzy Wavelet Based Textures Segmentation with a Single System Clock. Research Journal of Applied Sciences, Engineering and Technology, (07): 786-794.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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