Content based Image Retrieval for Medical Images using Canny Edge Detection Algorithm

Abstract

The rapid expansion of digital data content has led to the need for rich descriptions and efficient Retrieval Tool. To develop this, content based image Retrieval method has played an important role in the field of image retrieval. This paper aims to provide an efficient medical image data Retrieval from a huge content of medical database using one of the images content such as image shape, because, efficient content-based image Retrieval in the medical domain is still a challenging problem. The main objective of this paper is to provide an efficient tool which is used for efficient medical image retrieval from a huge content of medical image database and which is used for further medical diagnosis purposes.

The use of convolution operators in the tasks of edge detection

“…Суттєві результати в розвязку даної задачі досяг-нуті сучасними дослідниками в роботах [8][9][10][11], які пов'язані з лікуванням ракових захворювань, діагнос-тування тромбозу вен, результатами MP-ангіографії та для створення автопілотів для автомобілів [12].…”

Shape and Geometric Features-based Semantic Image Retrieval Using Multi-class Support Vector Machine

“…Currently, the retrieved of semantic images depends on keyword-based search. But there are silent numerous problems in Google search engines due to the absence of storing key and relationship among web images [16]. In natural image domain, the images with their features are stored in semantic manner to construct an ontological data set.…”

Comparing the Performance of Semantic Image Retrieval Using Sparql Query, Decision Tree Algorithm and Lire

“…The query may be in the form of an image, text-based or combination of two or more categories. The representation of acquired knowledge in the tree form is intuitive and generally easy to assimilate by humans (Ramamurthy and Chandran, 2011).…”