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The interferogram of multiple-beam Fizeau fringe technique plays an important role to investigate the optical properties of fiber because this interferogram provides us with useful information which can used to determine the dispersion curve of the fiber sample. A common problem in any interferogram analysis is the accuracy in locating fringe centers (fringe skeleton). There are a lot of computer-aided algorithms, which depend on the interferogram types, used to fringe skeleton extraction of various digital interferogram. In this paper, as far as I know, a novel algorithm for fringe skeleton extraction of double bright fringe of multiple-beam Fizeau fringe is presented. The proposed algorithm based on using the different order of Fourier transform and the derivative-sign binary image. Also the proposed algorithm has been successfully tested by using a computer simulation fringe and an experimental pattern. The results are compared with the original interferogram and shown a good agreement.

Nowadays, the intensive progress in development of laser sources and optical elements has challenged scientists to use the interferometry as an important diagnostic tool for accurate and gross field measurements of a various phenomena. These challenges have resulted in an accurate measurement in almost all engineering domains. For example in chemical engineering, materials science and physical fields, refractive index measurement is frequently needed.

There are many non-invasive interferometric techniques for measuring the refractive index profile and other related optical properties of fibers [1-4]. All of these techniques have their own advantages and disadvantages. The main advantages of these interferometric techniques, with respect to well established techniques, are that the sensitivity, accuracy, and non-contact characteristics. Furthermore, the most important of interferometric techniques over other techniques is that they are full-field, i.e. information about all points in the field can be recorded and observed simultaneously.

All of interferometric techniques based on the transformation of the phase differences of the wave fields, which is in turn related to a variety of physical properties, into observable intensity variation. In other words, the direct result of an interferometric technique is generally fringe pattern or interferogram. This interferogram provides us with rich quantitative information regarding sample material behavior.

In the past, the interferogram must be photographed and enlarged to a suitable magnification then the required data are obtained from the magnified image [5-8]. The manual quantitative analysis process is time consuming and very tedious, furthermore cannot make a full use of the interferogram’s data. For this reason, automatic image processing of these interferograms is an active topic in recent literature [9-11].

Recently, the trend has been toward the development of image processing algorithms capable of digitizing the image of the interferogram by using CCD camera. Each point is referred to as a pixel or picture element. The camera digitizes each pixel to a value between 0 (black) and 255 (bright) depends on the brightness of the pixel being digitized. The digital interferogram contains several millions of pixels. How to correctly interpret and make a full use of the digital interferogram data by eye is a big difficult task.

Over the last thirty years or so, due to the greet ability of the image processing techniques, there are a lot of computer-aided processing algorithms, which depend on the image types, that can be used to process various digital interferometric fringe patterns to enable semiautomatic or fully automatic analysis of the fringe pattern [12-18].

Because of the location of the geometric fringe centers or fringe skeleton are very convenient for fringe analysis. One of the basic steps in fringe analysis is to extract fringe center lines or the fringe skeleton. A number of methods for extracting the skeleton have been published and developed and many aspects of these techniques have been deeply investigated [19-24].

In short, although a variety of methods for extracting the fringe skeleton exist, these methods can be classified into two main groups. In the first group, the fringe pattern is first threshold to provide a binary gray level image. Then horizontal or vertical scan lines are used to determine the midpoints of each dark and bright region [

In the second group, the intensity variation within a fringe is used in devising algorithms for fringe skeleton determination by using two methods. The first method is a thinning algorithm which erodes the fringes from all sides [26-29]. The disadvantage of this algorithm is that it usually requires numerous iteration in order to peel the fringe pattern. The second method consists of differential filter techniques [24,30], this algorithm is very simple because it requires one step to find the center line of the fringe.

It is evident from the above paragraphs that the algorithm for determining the fringe center lines (skeletons) is a valuable task in the automatic fringe analysis technique and is still open.

Multiple-beam Fizeau interferometer is a well known technique frequently used to investigate the optical and structural properties of fiber [

In General, the multiple-beam Fizeau fringes characteristic by sharp bright fringe on a dark background^{31}, as shown in

In this paper all type of multiple-beam Fizeau fringe are fully automated for determination of the contour line using different order of Fourier transform technique.

The principle problem in accurately measuring the refractive index using multiple-beam Fizeau fringe system, is how to determine the contour line of the fringe pattern for; 1) interference fringe shift [

where

where r(x, y) is a fringe constant factor that depends on non-uniform illumination and reflection from the object surface, A_{n} is a Fourier coefficient, n is the order of the Fourier series, f_{o} is the carrier frequency, and j(x, y) is the phase of the object. The algorithm consists of four simple steps:

Step 1 Applying Fourier transform (FT) algorithm, we compute the one dimension (1-D) Fourier transform of Equation (1) for the variable x only, with y being fixed. The Fourier transform of Equation (1) is given by

where G(f, y) and Q_{n}(f, y) are the 1-D Fourier spectra of g(x, y) and q_{n}(x, y), respectively. It is clear from Equation (2) that the Fourier spectrum consists of many peaks. These peaks is generally separated by carrier frequency f_{o}.

Step 2 we select the suitable order component (this order depend on the interferogram as we will explain after) and the unwanted orders are filtered out.

and using the inverse Fourier transform, if we compute the inverse Fourier transform to Equation (3) with respect to f, the resulting function is a complex function. We select only the real part.

Step 3 we determine the derivative signs binary image [33,36] to the real part. In the binary image, if the deriva-

tive signs of the real part are positive, the points are setsto be a bright value. On the other hand, if the derivative signs of the real part are negative, the points are sets to be a dark value.

Step 4 After constructing the derivative sign binary image, it is easy to extract the fringe center lines using the following two steps: First, we select the positive peaks of the derivative sign and cancel the negative peaks by applying the threshold process over all the derivative sign binary image. Second examine each point neighborhood and quantify the slope then the result is the fringe center lines over the image field.

with its derivative sign. From

To verify this algorithm, first the algorithm was tested by using a computer simulated of multiple-beam Fizeau fringe in case of the refractive index of the immersion liquid is mismatching with the refractive index of the clad of the optical fiber, which shown in