Query-Based Image Retrieval using SVM

Ankit Kumar, Neha Janu
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引用次数: 1

Abstract

Now a day’s image plays an important role to extract the information about the object in various industries. Many traditional methods have been employed to retrieve images. It interactively determines the user’s query by asking the user whether the image is relevant or not. In this information tech age, graphics have become a major portion of information processing. In the Image registration processing, the image plays an important part to extract the information regarding the item in a variety of fields including in tourism, medical and geological, weather systems calling. There are lots of Approaches individuals who are used to recover images. It interactively determines an individual's query by requesting the users whether the image will be relevant (similar) or maybe not. In content-based image retrieval (CBIR) system, effective company of this image database used to improve the functioning of the procedure. The research of content-based image retrieval (CBIR) technique has become a significant research topic. Being an individual, we've Studied and done investigation of various features in this manner or in mixes. We found that image Registration processing (IRP) is the key area in above mentioned industries. Various research papers through color feature and texture feature extraction were studied and concluded that point cloud data structure is best for image registration process using Iterative Closest Point (ICP) algorithm.
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基于查询的SVM图像检索
如今,每天的图像在各行各业中都扮演着提取物体信息的重要角色。许多传统的方法被用来检索图像。它通过询问用户图像是否相关来交互式地确定用户的查询。在这个信息技术时代,图形已经成为信息处理的重要组成部分。在图像配准处理中,图像在旅游、医疗、地质、气象系统呼叫等多个领域对项目信息的提取起着重要的作用。有很多方法,个人谁是用来恢复图像。它通过询问用户图像是否相关(类似)来交互式地确定个人的查询。在基于内容的图像检索(CBIR)系统中,有效的利用了该图像数据库来改进程序的功能。基于内容的图像检索(CBIR)技术的研究已成为一个重要的研究课题。作为一个个体,我们以这种方式或混合的方式研究和调查了各种特征。我们发现图像配准处理(IRP)是上述行业的关键领域。通过对颜色特征和纹理特征提取的各种研究论文进行研究,得出点云数据结构最适合于使用迭代最近点(ICP)算法进行图像配准的结论。
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