A Multichannel Localization Method for Camouflaged Object Detection

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dc.contributor.advisorMd Shahriar Karim
dc.contributor.authorMohammad Rakibur Rahman
dc.contributor.authorMd Mafri Chowdhury
dc.contributor.authorMd Shohanur Rahaman Sarker
dc.contributor.id1812964042
dc.contributor.id1813393402
dc.contributor.id1812457402
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-04-17
dc.date.accessioned2025-04-17T05:09:13Z
dc.date.available2025-04-17T05:09:13Z
dc.date.issued2022
dc.description.abstractCamouflaged objects can be difficult to detect because they blend in with their surroundings. There have been numerous studies on detecting camouflaged objects, and many of these have been recognized as effective approaches. This paper presents a new algorithm for detecting camouflaged objects by focusing on identifying the region of interest, which is crucial for detecting these objects. The algorithm uses Phase Fourier Transformation to create a filtered image, and Entropy to generate a feature map from the filtered image. The feature map is then used to determine the region of interest. This paper proposes a multichannel method for discriminative region localization in Camouflaged Object Detection (COD) tasks. In one channel, processing the phase and amplitude of a 2-D Fourier spectrum generates modified form of the original image, used later for a pixel-wise optimal local entropy analysis. The other channel implements a class activation map (CAM) and Global Average Pooling (GAP) for object localization. We combine the channels linearly to form the final localized version of the COD images. Experimentation in multiple COD datasets demonstrates that the proposed method successfully localizes regions containing more than 80% of the camouflaged objects. Our proposed method does not require memoryintensive devices or prior training on particular image features, making it easily integrated into a resource-constrained environment. Theproposed approach is also applicable to non-COD images
dc.description.degreeUndergraduate
dc.identifier.cd600000493
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1117
dc.language.isoen
dc.publisherNorth South University
dc.rights© NSU Library
dc.titleA Multichannel Localization Method for Camouflaged Object Detection
dc.typeThesis
oaire.citation.endPage32
oaire.citation.startPage1
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