Many image acquisition techniques used in biomedical imaging, material analysis, and structural geology are capable of acquiring 3\u2013D solid images. Computational analysis of these images is complex but necessary since it is difficult for humans to visualize and quantify their detailed 3\u2013D content. One of the most common methods to analyze 3\u2013D data is to characterize the volumetric texture patterns. Texture analysis generally consists of encoding the local organization of image scales and directions, which can be extremely diverse in 3\u2013D. Current state\u2013of\u2013the\u2013 art techniques face many challenges when working with 3\u2013D solid texture, where most approaches are not able to consistently characterize both scale and directional information. 3\u2013D Riesz\u2013 wavelets can deal with both properties. One key property of Riesz filterbanks is steerability, which can be used to locally align the filters and compare textures with arbitrary (local) orientations. This paper proposes and compares three novel local alignment criteria for higher\u2013order 3\u2013D Riesz\u2013wavelet transforms. The estimations of local texture orientations are based on higher\u2013 order extensions of regularized structure tensors. An experimental evaluation of the proposed methods for the classification of synthetic 3\u2013D solid textures with alterations (such as rotations and noise) demonstrated the importance of local directional information for robust and accurate solid texture recognition. These alignment methods improved the accuracy of the unaligned Riesz descriptors up to 0.63, from 0.32 to 0.95 over 1 in the rotated data, which is better than all other techniques that are published and tested on the same database.<\/em><\/div>\n
<\/body><\/html><\/p>\n","protected":false},"excerpt":{"rendered":"
The journal article ‘3D Solid Texture Classification Using Locally-Oriented Wavelet Transforms’ is now available under the\u00a0‘Early Access’\u00a0area in IEEEXplore.\u00a0 The article will appear on the April issue of the IEEE Transactions on Image Processing journal.\u00a0 Abstract: Many image acquisition techniques used in biomedical imaging, material analysis, and structural geology are capable of acquiring 3\u2013D solid … <\/p>\n
Continue reading “Article on 3D solid texture classification now available in IEEEXplore”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"false","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-749","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p8AP2d-c5","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/749","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/comments?post=749"}],"version-history":[{"count":0,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/749\/revisions"}],"wp:attachment":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/media?parent=749"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/categories?post=749"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/tags?post=749"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}