{"id":6218,"date":"2011-11-09T14:18:51","date_gmt":"2011-11-09T12:18:51","guid":{"rendered":"http:\/\/hgpu.org\/?p=6218"},"modified":"2011-11-09T14:18:51","modified_gmt":"2011-11-09T12:18:51","slug":"parallel-implementation-of-niblacks-binarization-approach-on-cuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6218","title":{"rendered":"Parallel Implementation of Niblack&#8217;s Binarization Approach on CUDA"},"content":{"rendered":"<p>Image processing and pattern recognition algorithms take more time for execution on a single core processor. Graphics Processing Unit (GPU) is more popular now-a-days due to their speed, programmability, low cost and more inbuilt execution cores in it. Most of the researchers started work to use GPUs as a processing unit with a single core computer system to speedup execution of algorithms. The main goal of this research work is to make binarization faster for recognition of a large number of degraded document images on GPU. In this paper, parallel implementation is focused on the well known Niblack<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Image processing and pattern recognition algorithms take more time for execution on a single core processor. Graphics Processing Unit (GPU) is more popular now-a-days due to their speed, programmability, low cost and more inbuilt execution cores in it. Most of the researchers started work to use GPUs as a processing unit with a single core [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,73,89,33,3],"tags":[1787,1782,1791,14,1786,20,409,469],"class_list":["post-6218","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-computer-vision","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-computer-science","tag-computer-vision","tag-cuda","tag-image-processing","tag-nvidia","tag-nvidia-geforce-9500-gt","tag-pattern-recognition"],"views":2219,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6218","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6218"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6218\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6218"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6218"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}