人工智能
阈值
特征提取
模式识别(心理学)
图像纹理
局部二进制模式
计算机科学
特征(语言学)
计算机视觉
像素
特征检测(计算机视觉)
图像分割
二值图像
纹理(宇宙学)
图像处理
分割
图像(数学)
直方图
哲学
语言学
作者
Navneet Kaur,Nahida Nazir,Manik Rakhra
出处
期刊:International Conference on Computer Communications
日期:2021-09-03
被引量:16
标识
DOI:10.1109/icrito51393.2021.9596485
摘要
In the sphere of image processing, image data investigation is required related to a specific application in order to extract the suggestive information and reach defined and crisp culminations. One of the most significant phase in image processing is feature extraction which is the third step following image acquisition and segmentation. The procedure of reconstructing the input image into a group of features is named as feature extraction. These features construe the textural characteristics of the image. Texture feature extraction is one such significant part of feature extraction that on majority influences the results of classification. A texture is principally based on recognizing the object or region of interest in an image. The Local Binary Pattern feature descriptor will be the pith of discussion of this paper. LBP is a texture operator that operates on an image by labeling its pixels by thresholding neighborhood of each pixel. Various quality journals have been referred in order to provide an insight into the trends in pattern recognition using LBP.
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