PENGGABUNGAN CITRA SEL DARAH PADA MIKROSKOP DIGITAL
| Main Authors: | , MUCHAMMAD ARIEF ARIYANTO, , Ir. Balza Achmad, M.Sc.E. |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2013
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/124406/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=64538 |
Daftar Isi:
- Blood cell counting for diagnosing patient can be done automatically. One of many ways to count blood cells automatically is via Image Processing. However, the microscope which is used to take the image has its limits so that the images could not represent the sample, it only represents 1/9 part of the whole blood sample. The whole sample image must be taken more than once until it represents the whole sample. In consequences there is same blood cell in many images. The appearance of the same blood cell in many images makes the counting cannot be done effectively, because it will produce inaccurracy in counting. This research aims on making an image stitching program so that the counting can be performed well. One of possible methods that is used in image stitching is feature detection using SURF detector. The images that are stitched in this research are 16 images, which have 4x4 image formation. This program�s success rate is gained by comparing its result by its original image, wheter it represents them or not. The result of image stitching shows that image stitching program worked well for images with various color gradients. Index value of image result is varied by three categories, (1) method picked the index value from top-left images that is used as reference in geometrical operation, (2) method picked the average index value from image origin, and the last (3) method picked the highest index value from image origin. Method (1) gave 0.10% error value, while method (2) gave 2.27% error value, and method (3) gave 8.77 % error value. Keywords : Blood cell, feature detection, SURF detector, image stitching