|
What is 1000Projects
'1000projects.com' is an educational content website dedicated to finding and realizing Final Year Projects, IEEE Projects, Engineering Projects, Science Fair Projects, Project Topics, Project Ideas, Major Projects, Mini Projects, Paper Presentations, Presentation Topics, IEEE Topics, .Net Projects, Java Projects, PHP Projects, VB Projects, SQL Projects, C & DS Projects, C++ Projects, Perl Projects, ASP Projects, Delphi Projects, HTML Projects, Cold Fusion Projects, Java Script Projects, Btech Projects, BE Projects, MCA Projects, Mtech Projects, MBA Projects, Project on Software, CBSE Projects, Testing Projects, Embedded Projects, Chemistry Projects, Electronics Projects, Electrical Projects, Science Projects, Mechanical Projects, Mba project Reports, Placement papers, Sample Resumes, Entrance Exams, Technical Faq's, Puzzles, etc
how it works?
Everything on this site is submitted by the students in this professional community. You Can submit your Projects, Project Topics & Ideas to info.1000projects{at}gmail.com after you submit your project/project Idea/Abstract/Seminar Topics, These are being verified and approved by our administrator. after approval of this project/project Idea/Abstract/Seminar Topics, It can be shown on 1000projects.com so that other users can read/discuss it.The entire content on this website is Only For Educational Purpose, Non Commercial use!
Please help us/Other Users by sending projects/project Ideas/Abstracts/Seminar Topics. Thanking You!!!!!
|
EFFICIENT 2-D GRAY SCALE MORPHOLOGICAL TRANSFORMATIONS WITH ARBITRALY FLAT STRUCTURING ELEMENTS IMAGE PROCESSING DOT NET An efficient algorithm is presented for the computation of grayscale morphological operations with arbitrary 2-D flat structuring elements (S.E.). The required computing time is independent of the image content and of the number of gray levels used. It always outperforms the only existing comparable method, which was proposed in the work by Van Droogen broeck and Talbot, by a factor between 3.5 and 35.1, depending on the image type and shape of S.E. So far, filtering using multiple S.E.s is always done by performing the operator for each size and shape of the S.E. separately. With our method, filtering with multiple S.E.s can be performed by was proposed in the work by Van Droogen broeck and Talbot, by a factor between 3.5 and 35.1, depending on the image type and shape of S.E. So far, filtering using multiple S.E.s is always done by performing the operator for each size and shape of the S.E. separately. With our method, filtering with multiple S.E.s can be performed by a single operator for a slightly reduced computational cost per size or shape, which makes this method more suitable for use in granulometries, dilation-erosion scale spaces, and template matching using the hit-or-miss transform. The discussion focuses on erosions and dilations, from which other transformations can be derived. a single operator for a slightly reduced computational cost per size or shape, which makes this method more suitable for use in granulometries, dilation-erosion scale spaces, and template matching using the hit-or-miss transform. The discussion focuses on erosions and dilations, from which other transformations can be derived.
|