Efficient Implementation of Mean Formula for Image Processing using FPGA Device

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Efcient Implementation

of Mean Formula for Image

Processing

using FPGA Device

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Introduction

Digital image processing is a proses for manipulating and analysing image with computer.

Image processing can be divided into two kind of activities :

 Increasing the quality of image for easy interpretation by human eye, this activity known as image enhancement

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Previous Research

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Some image processing uses basic statistic formula such as :

histogram, mean, variance, etc. In embedded environtment those formula must be implemented in hardware base, like FPGA for example.

A research for histogram calculation for 8x8 image need 256 addition,

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Previous Research

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 Other research for histogram and mean calculation base on

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IMAGE PROCCESSING FORMULA

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Histogram Formula

Image histogram is a diagram that draw frequency of the appearance every intensity value from the whole image pixel element. The higher value of histogram show the number of pixels with that intensity value is high and vice versa. Histogram can show the brightness and contrast of the image. A lot of use histogram in image texture analysis because of the simplicity of the algorithm.

Histogram mathematical formula is :

H(i) is histogram of the image with NxM size and

i is intensity value of the pixel in the image.

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Example of a histogram diagram comming from several

image.

http://www.freeimages.com/search/texture

Histogram smooth texture

Histogram regular texture

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IMAGE PROCCESSING FORMULA

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 _{From the histogram value we can calculate the}_‘mean’_{value from the} image.

 _{Mathematical formula for ‘}_mean_{’ (µ) is :}

 In this formula i is grey level of intensity pixel in the image and p(i) is the probability of occurence i.

 _L _{is the higher value of grey level i. This formula will produce an} average brightness of objects

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Pixel Image (NxM)

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AGORITHM (1)

 Mean is the frst-order statistical analysis methods used for segmentation and feature extraction processes an image.

Psudo code 1. Mean formula ( 1st version)

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 Referring to the equation (2) and (1) where the mean is calculated by using the calculation result histogram, equation (3) is proposed :

 _{Psudo code 2 is the revised algorihtm with some} _efciency,

reducing the loop and mathematical operation.

PROPOSED ALGORITHM (2)

Psudo code 2. Mean formula ( revised version)

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Result Matlab

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HARDWARE IMPLEMENTATION (1)

 Component design for psudo code[1] :

• _{Shown in the picture, is the frst design based on frst pseudo}

code, this design need a selector to select intensity value of pixel from the image between 0 to 255 and send to thier respective accummulator (256 accumulator with 256 addition component).

• _{All these accumulator value will be send to 256 input}

addition (or another 256 addition),

• _{So we need 512 addition for this design. And fnnally to}

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HARDWARE

IMPLEMENTATION

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 _{Component design for psudo code[2] :}

• _{Further, shown in the picture is new design of the design of the}

previous image.

• _{To calculate mean value actually we don’t have to calculate}

histogram, to hold the total value of pixel element value

(htsum) in the 2nd pseudo code

• _{This approach give us the reduction of mathematical operation}

(component)

• _{This design only need one addition in one accumulator and one}

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Entity Diagram of efficient component

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Simulation result for proposed

component

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CONCLUSSION

 The efcient implementation of mean formula into harware

base compponent using FPGA device has been proposed.

 _{This component use one addition and one shift right register}

with 64 clock cycles to calculate mean value for 8x8 image size.

 This design needs 14 slices of fip-fops and 14 of 4 input

LUTs.

 The diference (as an error) of mean value comparing to

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References

Nitin Sachdeva and Tarun Sachdeva,“ An FPGA Based Real-time Histogram Equalization Circuit for Image Enhancement”, International Journal of Electronics and Communication Technology (IJECT) Vol 1 Issue 1 December 2010.

Atit Pertiwi, “Optimalisasi Metode Implementasi Algoritma Histogram, Mean Dan Variansi Ke Dalam IC-FPGA Untuk Aplikasi Analisis Tekstur Citra Real Time”, Disertasi, Teknologi Informasi, Universitas Gunadarma, 2015.

Luca Maggiani, Claudio Salvadori, Matteo Petracca, Paolo Pagano, Roberto Saletti, “Reconfgurable Archictecture for Computing Histograms in Real-Time Tailored to FPGA-based Smart Camera”, Industrial Electronics (ISIE), IEEE 23rd International Symposium on , Istambul Turkey, June 2014.

_{Wendy L. Martinez and Angel R. Martinez, “Computational Statistics Handbook}

with MATLAB”, Chapman & Hall/CRC, USA, 2002.

R.E. Woods , S.L. Eddins , dan R.C. Gonzales, “Digital Image Processing Using MATLAB . Pearson Educatio, 2005.

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