Improvement of Classification Accuracy Using Image Fusion Techniques

Singh, Rajesh; Gupta, Rajiv

doi:10.1109/iccia.2016.21

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…The technique was found to work well for standardimagesize,butinreality,hugesetofimageswithvaryingsizesandparametersexists, where the proposed methodology may be inappropriate. The authors in (Singh et al, 2016) developed an accuracy prediction method for spatial images specifically satellite image data wheretheclassificationaccuracyoftheimagesbeforefusing(originalimage)andfusedimage iscalculated.However,theworkdoesnotmentionanymethodologydevelopedtoensurethe securityoftheimagesstored.In(Sundaratal.,2017)theauthorsdevelopedamulti-sensorimage fusiontechniqueusingwavelettransformsuitableforobjectrecognitionanddestinationprediction (Kumaratal.,2015).Theexpansionofcloudresultedinallowingthevariousorganizationsto empoweringtheircustomers.Thisupgradethehealthcareservicesandcanbenefitresearchin healthcare (Asijaatal.,2016).Theretrievalsystemperformstheidentificationofsamedataof imagebypassingcharacterrecognitionmechanism.Italsoprovideresponseagainstdifferent queries (Tavoli et al, 2013). The prime benefit for applying encryption is that it allows in performinganarbitrarynumberoffunctionsonthedatathatisencryptedusingsecuresecret keyoftheuser.Allthisisbecauseofthecomputationalcapabilityofhomomorphicencryption (Ibtihaletal.,2017).Authors(ZhenLietal.,2017;Shekhar2018)proposedasecureTTP-free andchannel-freeMSEscheme.Theintroductionofadesignatedservermakesitsecureagainst keyword guessing attack.…”

Section: Related Workmentioning

confidence: 99%

Design of Secure Image Fusion Technique Using Cloud for Privacy-Preserving and Copyright Protection

Kumar¹

2019

International Journal of Cloud Applications and Computing

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Nowadays, the use of digital content or digital media is increasing day by day. Therefore, there is a need to protect the digital document from both unauthorized users and authorized users. The digital document should be protected from authorized users who try to redistribute it illegally. Digital watermarking techniques along with cryptography are insufficient to ensure an adequate level of security of digital media. The security of the transferring digital data in the modern world is also a big challenge because there is a high risk of security breaches. In this article, a secure technique of image fusion using hybrid domains (spatial and frequency) for privacy preserving and copyright protection is proposed. The proposed method provides a secure technique for the digital content in cloud environment. Two cloud services are used to develop this work, which eliminates the role of a trusted third party (TTP). First is the design of an infrastructure as a service (IaaS) to store different images with encryption processes to speed up the image fusion process and save storage space. Second, a Platform as a Service (PaaS) is used to enable the digital content to improve computation power and to increase the bandwidth. The prime objective of the proposed scheme is to transfer the digital media between a service provider and customer in a secure way using a hybrid domain along with cloud storage. Imperceptibility and robustness measures are used to calculate the performance of the proposed approach.

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Section: Related Workmentioning

confidence: 99%

Design of Secure Image Fusion Technique Using Cloud for Privacy-Preserving and Copyright Protection

Kumar¹

2019

International Journal of Cloud Applications and Computing

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“…While there are many studies in image fusion for the visual enhancement of images, very few types of research focus on the influence of image fusion in other applications such as image classification. The role of image fusion in remote sensing is significant, and almost every recent sensor development for earth applications considers channels with different spatial resolutions [ 7 , 8 ]. Image fusion improves the information content by combining two or more images using a specific algorithm [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine

Nanmaran

Srimathi

Yamuna

et al. 2022

Computational and Mathematical Methods in Medicine

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Image fusion can be performed on images either in spatial domain or frequency domain methods. Frequency domain methods will be most preferred because these methods can improve the quality of edges in an image. In image fusion, the resultant fused images will be more informative than individual input images, thus more suitable for classification problems. Artificial intelligence (AI) algorithms play a significant role in improving patient’s treatment in the health care industry and thus improving personalized medicine. This research work analyses the role of image fusion in an improved brain tumour classification model, and this novel fusion-based cancer classification model can be used for personalized medicine more effectively. Image fusion can improve the quality of resultant images and thus improve the result of classifiers. Instead of using individual input images, the high-quality fused images will provide better classification results. Initially, the contrast limited adaptive histogram equalization technique preprocess input images such as MRI and SPECT images. Benign and malignant class brain tumor images are applied with discrete cosine transform-based fusion method to obtain fused images. AI algorithms such as support vector machine classifier, KNN classifier, and decision tree classifiers are tested with features obtained from fused images and compared with the result obtained from individual input images. Performances of classifiers are measured using the parameters accuracy, precision, recall, specificity, and F 1 score. SVM classifier provided the maximum accuracy of 96.8%, precision of 95%, recall of 94%, specificity of 93%, F 1 score of 91%, and performed better than KNN and decision tree classifiers when extracted features from fused images are used. The proposed method results are compared with existing methods and provide satisfactory results.

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Integration of High Spectral and High Spatial Resolution Image Data for Accurate Target Detection

Chakravortty¹,

Das²

2017

Communications in Computer and Information Science

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Improvement of Classification Accuracy Using Image Fusion Techniques

Cited by 8 publications

References 9 publications

Design of Secure Image Fusion Technique Using Cloud for Privacy-Preserving and Copyright Protection

Design of Secure Image Fusion Technique Using Cloud for Privacy-Preserving and Copyright Protection

Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine

Integration of High Spectral and High Spatial Resolution Image Data for Accurate Target Detection

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