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Content Based Image Retrieval Using Color Layout Descriptor and Generic Fourier Descriptor

机译:基于内容的图像检索使用颜色布局描述符和通用傅立叶描述符

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Image databases have been a significant part of systems or applications in many fields including education, forensics and medical sciences. However, due to the increase in the number of digital resources especially images, the demand to manage these databases such as storing and retrieving the images effectively and efficiently from these databases is crucial. Content Based Image Retrieval (CBIR) is one of the best techniques used to retrieve similar images from the image database. Even though it is a good and well-researched technique, still there are some issues to be improved. One of the challenges in CBIR is to represent the image as a feature vector. In this paper, we proposed a new feature vector using Generic Fourier Descriptor (GFD) and Color Layout Descriptor (CLD) to increase the accuracy of the retrieval process. We tested our technique with the Coral Database and compared the results with other CBIR techniques. Proposed method achieved better results than previous techniques. The proposed technique can be used by the forensic department for identification of criminal suspect using forensic database.
机译:图像数据库是许多领域的系统或应用程序的重要组成部分,包括教育,取证和医学科学。然而,由于尤其是图像的数字资源数量的增加,需要管理和从这些数据库有效且有效地存储和检索图像的数据库的需求至关重要。基于内容的图像检索(CBIR)是用于从图像数据库检索类似图像的最佳技术之一。即使它是一种良好且经过良好的技术,仍有一些问题需要得到改善。 CBIR中的一个挑战是将图像代表为特征向量。在本文中,我们提出了一种使用通用傅里叶描述符(GFD)和颜色布局描述符(CLD)的新特征向量,以提高检索过程的准确性。我们用珊瑚数据库测试了我们的技术,并将结果与​​其他CBIR技术进行了比较。提出的方法比以前的技术实现了更好的结果。法医部门可以使用所提出的技术来使用法医数据库确定犯罪嫌疑人。

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