Suatu proses klasifikasi citra berbasis analisis tekstur pada umumnya membutuhkan tahapan ekstraksi ciri, yang terdiri dari tiga macam metode yaitu metode statistik, metode spaktral dan metode struktural. Metode GLCM termasuk dalam metode statistik dimana dalam perhitungan statistiknya menggunakan distribusi derajat keabuan histogram dengan mengukur tingkat kekontrasan, granularitas, dan kekasaran suatu daerah dari hubungan ketetanggaan antar piksel di dalam citra. Paradigma statistik ini penggunaannya tidak terbatas, sehingga sesuai untuk tekstur-tekstur alami yang tidak terstruktur dari sub pola dan himpunan aturan mikrostruktur. Metode statistik terdiri dari ekstraksi ciri orde pertama dan ekstraksi ciri orde kedua. Ekstraksi ciri orde pertama dilakukan melalui histogram citra sedangkan ekstraksi ciri statistik orde kedua dilakukan dengan matriks kookurensi, yaitu suatu matriks antara yang merepresentasikan hubungan ketetanggaan antar piksel dalam citra pada berbagai arah orientasi dan jarak spasial. Ilustrasi ekstraksi ciri statistik ditunjukkan pada gambar 1.

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Select the distance between the reference and neighbor sample samples. Given an image composed of pixels each with an intensity a specific gray level , the GLCM is a tabulation of how often different combinations of gray levels co-occur in an image or image section.

Texture feature calculations use the contents of the GLCM to give a measure of the variation in intensity a. Echoview offers a GLCM Texture Feature operator that produces a virtual variable which represents a specified texture calculation on a single beam echogram. Algorithm The virtual variable is created in the following way using the settings on the GLCM Texture page of the Variable properties dialog box identified in bold : Quantize the image data. Each sample on the echogram is treated as a single image pixel and the value of the sample is the intensity of that pixel.

These intensities are then further quantized into a specified number of discrete gray levels as specified under Quantization. Create the GLCM. It will be a square matrix N x N in size where N is the Number of levels specified under Quantization.

The matrix is created as follows: Let s be the sample under consideration for the calculation. Let W be the set of samples surrounding sample s which fall within a window centered upon sample s of the size specified under Window Size. Considering only the samples in the set W, define each element i,j of the GLCM as the number of times two samples of intensities i and j occur in specified Spatial relationship where i and j are intensities between 0 and Number of levels The sum of all the elements i, j of the GLCM will be the total number of times the specified spatial relationship occurs in W.

As a consequence the sum of all the elements i, j of the GLCM will now be twice the total number of times the specified spatial relationship occurs in W once where the sample with intensity i is the reference sample and once where the sample with intensity j is the reference sample , and for any given i, the sum of all the elements i, j with the given i will be the total number of times a sample of intensity i appears in the specified spatial relationship with another sample.

Calculate the selected Feature. This calculation uses only the values in the GLCM.

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## GLCM Texture Feature

Select the distance between the reference and neighbor sample samples. Given an image composed of pixels each with an intensity a specific gray level , the GLCM is a tabulation of how often different combinations of gray levels co-occur in an image or image section. Texture feature calculations use the contents of the GLCM to give a measure of the variation in intensity a. Echoview offers a GLCM Texture Feature operator that produces a virtual variable which represents a specified texture calculation on a single beam echogram. Algorithm The virtual variable is created in the following way using the settings on the GLCM Texture page of the Variable properties dialog box identified in bold : Quantize the image data.

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## Select a Web Site

The graycomatrix function creates a gray-level co-occurrence matrix GLCM by calculating how often a pixel with the intensity gray-level value i occurs in a specific spatial relationship to a pixel with the value j. By default, the spatial relationship is defined as the pixel of interest and the pixel to its immediate right horizontally adjacent , but you can specify other spatial relationships between the two pixels. Each element i,j in the resultant glcm is simply the sum of the number of times that the pixel with value i occurred in the specified spatial relationship to a pixel with value j in the input image. Because the processing required to calculate a GLCM for the full dynamic range of an image is prohibitive, graycomatrix scales the input image.

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## Pemrograman Matlab

Vizuru Although this tutorial is not published by a professional journal, it has undergone extensive peer review by third-party reviewers at the request of the author. Background information is provided to answer the questions arising from 15 years of use of the tutorial, and increased practical experience of the author in teaching and research. Metadata Show full item record. This GLCM texture tutorial was developed to help such people, and it has been used extensively world-wide since You specify gglcm offsets as a p -by-2 array of integers.