Image Mining: An Overview of Current Research

Khodaskar, Anuja; Ladhake, S. A.

doi:10.1109/csnt.2014.93

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…The seamless integration of preprocessing, feature extraction, DM, and interpretation stages exemplifies a comprehensive approach to IM, advancing a deeper understanding of the underlying visual data and enabling informed decision-making in the need for an approach to enhance the robustness and efficacy of the image retrieval process [9]. In IM, the selection of semantic features depends on the specific goals of the task, the characteristics of the images, and the nature of the information the user wants to extract [10].…”

Section: Figure 1 General Structure Of Immentioning

confidence: 99%

T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

Thanikachalam,

Thavasimuthu,

Arulkumar

et al. 2024

Preprint

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In the field of Image Mining (IM) and Content-Based Image Retrieval (CBIR), the significance lies in extracting meaningful information from visual data. By focusing on the intrinsic meaning within images, semantic features enhance the accuracy and relevance of image retrieval systems, bridging the gap between human understanding and computational analysis in visual data exploration. This research explores the fusion of image processing techniques and CBIR. The need for this research is based on the persistent challenges in existing CBIR systems, where traditional methods often fall short of comprehensively capturing the intricate semantics of images. The primary objective of this research is to propose a novel approach to CBIR by implementing the Tokens-to-Token Vision Transformer (T2T-ViT) to address the limitations of traditional CBIR systems and enhance the accuracy and relevance of image retrieval. The T2T-ViT model achieves exceptional performance in CBIR on Corel datasets, with a high accuracy of 99.42%, precision of 98.66%, recall of 98.89%, and F-measure of 99.35%. The model demonstrates a harmonious balance between identifying and retrieving relevant images compared to existing models.

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Section: Figure 1 General Structure Of Immentioning

confidence: 99%

T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

Thanikachalam,

Thavasimuthu,

Arulkumar

et al. 2024

Preprint

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“…Image mining is use in various fields. Different applications of image are; [2,3,5,6 [8]: It involves satellite images. Satellite images are a significant source of information.…”

Section: Image Mining Applicationsmentioning

confidence: 99%

“…Research in Image mining can be broadly classified in two main directions (1) Domain specific applications (2) General applications [2].Image Mining is different from computer vision, and image processing techniques. This is because the focus of image mining is in the extraction of patterns from a large collection of images, whereas the focus of computer vision and image processing techniques is in understanding and/or extracting specific features from a single image [3]. Variety of image data for instance digital photographs, medical images and satellite TV images are generally generated each day.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Image Mining, its Techniques and Application

Shukla¹,

Vala²

2016

IJCA

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We know that today's world is digital world and we have use digital data such as video, audio, images etc. in various fields for various purposes. In present scenario, image plays vital role in every aspect of business such as business images, satellite images, and medical images and so on. Image mining is challenging field which extends traditional data mining from structured data to unstructured data such as image data. The main aim of this paper is to present a survey of the various techniques used for image mining applications. Forests fires are a significant problem. To fight against these disasters, the accurate prediction of forest fire is a crucial issue. The increase in the number of forest fires in the last few years has forced governments to take precautions. If the fire fighters know where the fire will be in sometimes it would be easier for them to stop the fire. Therefore a big need for predicting the fire behavior exists. In this paper various techniques of image mining and different algorithms used to analyze a key event-fire is studied. This paper covers literature survey of image mining techniques and its applications.

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“…This issue demanded a simpler approach for image mining (Jain et al, 2013). Thus, the technique of image mining (Banda et al, 2014;Chen and Mei, 2014) was divided into four important phases: image pre-processing, feature extraction, conversion of image database to transaction database, and applying association rule mining (Wang et al, 2014;Herold et al, 2011;Khodaskar and Ladhake, 2014) to this transaction database. The proposed new association rule algorithm (Deshpande, 2010) reduced the number of scans for a priori algorithm.…”

Section: Association Rule Miningmentioning

confidence: 99%

Image mining framework and techniques: a review

Dey¹,

KarÁ¢a²,

Chakraborty³

et al. 2015

IJIM

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Abstract:Image mining refers to a data mining technique where images are used as data. It supports a large field of applications like medical diagnosis, agriculture, industrial work, space research and obviously the educational field. The image mining technique can extract knowledge and exciting patterns which are not stored in the database by analysing the images using various tools. The new era of advanced technology and high storage capability supports the growth of large and detailed image database. This review paper presents a detailed view on the existing research works in the area of image mining and also summarised the different techniques used.

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Image Mining: An Overview of Current Research

Cited by 7 publications

References 14 publications

T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

T2T-ViT: A Novel Semantic Image Mining Approach for Improving CBIR Using Vision Transformer

A Survey on Image Mining, its Techniques and Application

Image mining framework and techniques: a review

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