Object Detection and Recognition Using Local Quadrant Pattern Testing on The Skin Cancer Region

A. Hashim
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引用次数: 1

Abstract

Object detection and recognition is one of the important techniques in computer vision for searching and scanning and identifying an object in images or videos. Object detection and recognition enters into many important fields where one of the uses of object detection and recognition is to detect region of injury and determine the type of injury. This paper suggested a new effective method called Local Quadrant Pattern (LQP). The proposed method uses a window and passes it on all pixels of the image and uses the pixel direction to arrange the adjacent pixels. It also uses four code values to encode and then produce a texture feature matrix which is used to detect objects as well as extract features based on magnitude of pixels for image classification. The experiments were conducted on the infected regions in the skin and the results showed the ability of the method to detect regions of infection as well as the high accuracy in the classification of those regions. Keywords— Local Quadrant Pattern (LQP), Object Detection, Threshold, Local Ternary Pattern (LTP), Skin, Cancer
基于局部象限模式测试的皮肤癌区域目标检测与识别
目标检测与识别是计算机视觉中搜索、扫描和识别图像或视频中的目标的重要技术之一。目标检测与识别进入了许多重要的领域,其中目标检测与识别的用途之一就是检测损伤区域并确定损伤类型。本文提出了一种新的有效方法——局部象限图。该方法使用一个窗口并将其传递到图像的所有像素上,并使用像素方向排列相邻像素。利用4个码值进行编码,生成纹理特征矩阵,用于检测目标,并根据像素大小提取特征进行图像分类。在皮肤感染区域进行了实验,结果表明该方法能够检测感染区域,并且在这些区域的分类中具有很高的准确性。关键词:局部象限模式(LQP),目标检测,阈值,局部三元模式(LTP),皮肤,癌症
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