MERAL Myanmar Education Research and Learning Portal
Item
{"_buckets": {"deposit": "e2a97e7a-12ea-4b37-bbb8-252f51b1010f"}, "_deposit": {"created_by": 92, "id": "7465", "owner": "92", "owners": [92], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "7465"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00007465", "sets": ["user-miit"]}, "communities": ["miit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Automatic Image Segmentation Using Edge and Marker Controlled Watershed Transformation", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Image segmentation has been a difficult task in computer vision. The role of image segmentation is to decompose an image into parts that are meaningful with respect to the particular applications. Subsequent methods for image description, recognition, image visualization, image compression, highly depend on the segmentation results obtained from previous stage. Therefore, we propose an automatic image segmentation method by combining an edge detection technique with modified mask as a preprocessing method and Marker Controlled Watershed Transformation (MCWT) for final image segmentation. In this paper, watershed algorithm with modified Laplacian of Gaussian (LoG) edge detector is used to detect\nthe gradient image of input image and produce the image which is less sensitive to noise. In order to get final image with less over segmentation, it is helped by MCWT. Therefore, our proposed method has also been observed a satisfactory segmentation image with better edges and with less over segmentation."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Laplacian of Gaussian filter"}, {"interim": "Zero Crossing"}, {"interim": "Watershed algorithm"}, {"interim": "Marker-controlled watershed Transformation"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2021-01-14"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ICAET 2014.pdf", "filesize": [{"value": "1.3 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_0", "mimetype": "application/pdf", "size": 1300000.0, "url": {"url": "https://meral.edu.mm/record/7465/files/ICAET 2014.pdf"}, "version_id": "e512e670-1379-44ed-9b92-5e92e1610fe4"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICAET 2014", "subitem_c_date": "3/29/2014", "subitem_conference_title": "IIE INT\u0027L Conference Proceedings of International Conference on Advances in Engineering and Technology (ICAET\u00272014)", "subitem_part": "Session 1 (pp-100-104)", "subitem_place": "Singapore", "subitem_session": "Session 1", "subitem_website": "https://pdfs.semanticscholar.org/a9a4/60aa352f61661dedf9aab3ad33043361f6cc.pdf"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Khin Lay Mon"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2014-03-30"}, "item_title": "Automatic Image Segmentation Using Edge and Marker Controlled Watershed Transformation", "item_type_id": "21", "owner": "92", "path": ["1582963674932", "1597397014014"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000007465", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2021-01-14"}, "publish_date": "2021-01-14", "publish_status": "0", "recid": "7465", "relation": {}, "relation_version_is_last": true, "title": ["Automatic Image Segmentation Using Edge and Marker Controlled Watershed Transformation"], "weko_shared_id": -1}
Automatic Image Segmentation Using Edge and Marker Controlled Watershed Transformation
http://hdl.handle.net/20.500.12678/0000007465
http://hdl.handle.net/20.500.12678/0000007465cd429863-cd13-46e3-870f-50207a16c9e1
e2a97e7a-12ea-4b37-bbb8-252f51b1010f
Name / File | License | Actions |
---|---|---|
ICAET 2014.pdf (1.3 MB)
|
Publication type | ||||||
---|---|---|---|---|---|---|
Conference paper | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Automatic Image Segmentation Using Edge and Marker Controlled Watershed Transformation | |||||
Language | en | |||||
Publication date | 2014-03-30 | |||||
Authors | ||||||
Khin Lay Mon | ||||||
Description | ||||||
Image segmentation has been a difficult task in computer vision. The role of image segmentation is to decompose an image into parts that are meaningful with respect to the particular applications. Subsequent methods for image description, recognition, image visualization, image compression, highly depend on the segmentation results obtained from previous stage. Therefore, we propose an automatic image segmentation method by combining an edge detection technique with modified mask as a preprocessing method and Marker Controlled Watershed Transformation (MCWT) for final image segmentation. In this paper, watershed algorithm with modified Laplacian of Gaussian (LoG) edge detector is used to detect the gradient image of input image and produce the image which is less sensitive to noise. In order to get final image with less over segmentation, it is helped by MCWT. Therefore, our proposed method has also been observed a satisfactory segmentation image with better edges and with less over segmentation. |
||||||
Keywords | ||||||
Laplacian of Gaussian filter, Zero Crossing, Watershed algorithm, Marker-controlled watershed Transformation | ||||||
Conference papers | ||||||
ICAET 2014 | ||||||
3/29/2014 | ||||||
IIE INT'L Conference Proceedings of International Conference on Advances in Engineering and Technology (ICAET'2014) | ||||||
Session 1 (pp-100-104) | ||||||
Singapore | ||||||
Session 1 | ||||||
https://pdfs.semanticscholar.org/a9a4/60aa352f61661dedf9aab3ad33043361f6cc.pdf |