CBIR System Development Using the Concepts of Image Feature Synthesis with Matching Parameters-A Survey

Battur, Ranjana; Jagadisha, N

doi:10.46610/jocei.2021.v07i01.006

Cited by 1 publication

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“…This refers to the fact that images can vary in terms of their angle, scale, lighting conditions, and other factors. This can make it difficult for CBIR systems to accurately match images, even if they contain the same objects [11]. Additionally, images often contain multiple objects, and it can be difficult for CBIR systems to identify the subject of interest [12].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Content-based Image Retrieval System using Logical AND and OR Operations

Battur,

Narayana

2023

IJACSA

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This paper proposes an innovative ensemble learning framework for classifying medical images using Support Vector Machine (SVM) and Fuzzy Logic classifiers. The proposed approach utilizes logical AND and OR operations to combine the predictions from the two classifiers, aiming to capitalize on the strengths of each. The SVM and Fuzzy Logic classifiers were independently trained on a comprehensive database of medical images comprising various types of X-ray images. The logical OR operation was then used to create an ensemble classifier that outputs a positive classification if either of the individual classifiers does so. On the other hand, the logical AND operation was used to construct an ensemble classifier that outputs a positive classification only if both individual classifiers do so. The proposed method aims to increase sensitivity and precision by capturing as many positive instances as possible, thereby reducing false positives. The scope of the proposed work is validated in terms of overall time complexity and retrieval accuracy. The simulation outcome shows promising result with 98.36 accuracy score and 1.8 seconds to retrieve all the images in query database.

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Section: Introductionmentioning

confidence: 99%