GLCM Based Locally Feature Extraction On Natural Image
نویسندگان
چکیده
GLCM is a feature extraction method that uses statistical analysis using gray scale. Contrast, correlation, energy and entropy are features whose value will be sought as the basis for finding threshold which can then used to find in image segmentation. In this study, local-based where has been made into grayscale divided 16 parts of same size. Each section look its features, namely entropy. The calculation these four applied image, value. results with an angle 0o contrast = 0.0080, correlation 0.619, : 0.00160 0.05591.
منابع مشابه
Natural Scene Image Segmentation Based on Multi-Layer Feature Extraction
This paper addresses the problem of natural image segmentation by extracting information from a multi-layer array which is constructed based on color, gradient, and statistical properties of the local neighborhoods in an image. A Gaussian Mixture Model (GMM) is used to improve the effectiveness of local spectral histogram features. Grouping these features leads to forming a rough initial over-s...
متن کاملSurvey: Image Mosaicing based on Feature Extraction
Image Mosaicing is as an consider in and personal digital assistant graphics. Image stitching is by the whole of two or images of the close study which is called panoramic image. Image stitching techniques are categorized two approaches: Direct and feature based techniques. Direct techniques link the pixel intensities of the images by all of each whereas based techniques to a mid the images all...
متن کاملAnalysis of Skin Cancer Classification Using GLCM Based On Feature Extraction in Artificial Neural Network
Skin cancer is the deadliest form of cancers in humans. Skin cancer is commonly known as Melanoma. Skin Cancers are of two typesBenign and Malignant Melanoma. Melanoma can be cured completely if it is detected early. Both benign and malignant melanoma appear in similar. So it is difficult to differentiate both. This is a main problem with the early skin cancer detection. Only an expert dermatol...
متن کاملShift and Rotation Invariant Iris Feature Extraction based on Non-subsampled Contourlet Transform and GLCM
A new feature extraction method for iris recognition in non-subsampled contourlet transform (NSCT) domain is proposed. To extract the features a two-level NSCT, which is a shift-invariant transform, and a rotation-invariant gray level co-occurrence matrix (GLCM) with 3 different orientations are applied on both spatial image and NSCT frequency subbands. The extracted feature set is transformed ...
متن کاملComments on "On Image Matrix Based Feature Extraction Algorithms"
A class of image-matrix-based feature extraction algorithms has been discussed earlier. The correspondence argues that 2-D principal component analysis and Fisher linear discriminant (FLD) are equivalent to block-based PCA and FLD. In this correspondence, we point out that this statement is not rigorous.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: JAIS (Journal of Applied Intelligent System)
سال: 2022
ISSN: ['2502-9401', '2503-0493']
DOI: https://doi.org/10.33633/jais.v7i2.6569