Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mahmut Kılıçaslan"'
Autor:
Mahmut Kılıçaslan, Mürsel Ozan İncetaş
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-23 (2023)
Abstract In this study, a novel color quantization approach which automatically estimates the number of colors by multi-level thresholding based on the histogram is proposed. The method consists of three stages. First, red–green–blue is clustered
Externí odkaz:
https://doaj.org/article/4381af4224504e17a25a22b477f4853b
Publikováno v:
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Vol 8, Iss 1, Pp 1042-1057 (2020)
Sayısal görüntülerden oluşan bir veri tabanından sorgulanan bir görüntünün aynısının veya benzerlerinin getirilmesi süreci görüntü erişimi olarak tanımlanır. Her ne kadar sayısal görüntü piksellerden oluşuyor olsa da sorgulam
Externí odkaz:
https://doaj.org/article/7e52b59091e04b678d0092fd356d6a42
Publikováno v:
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Vol 6, Iss 4, Pp 1094-1107 (2018)
Histogram sayısal görüntülerdeki piksellerin dağılımını gösteren önemli bir bilgi temsil yöntemidir. Gri seviyeli görüntülerde tek boyutlu dizi işlenirken, renkli görüntülerde üç boyutlu dizinin analizinin yapılması gereklidir.
Externí odkaz:
https://doaj.org/article/d5adb57c604b42acb38e30aa07a27a46
Publikováno v:
Advances in Electrical and Computer Engineering, Vol 20, Iss 2, Pp 79-88 (2020)
Image histograms are frequently used as a feature vector in content-based image retrieval (CBIR). The related methodology involves processing of a single channel histogram on gray level images while histograms of three channels must be processed in c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cf458474679447c6846fcb67f607d46
https://doaj.org/article/5b6f4c6844f34e049fc04083ebbc3bb7
https://doaj.org/article/5b6f4c6844f34e049fc04083ebbc3bb7
Publikováno v:
Volume: 8, Issue: 1 1042-1057
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Image retrieval is defined as the process of retrieving same or similar of an image queried from a digital image database. Although a digital image is composed of pixels, the query is not performed at the pixel level but it is carried out at level of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08b68a58e1c03dd911faddf79719af44
https://doi.org/10.29130/dubited.643351
https://doi.org/10.29130/dubited.643351
Autor:
Mahmut Kılıçaslan, Recep Demirci
Feature extraction is fundamental stage of effective content based image retrieval (CBIR). However, it remains challenging issue to extract low-level features for retrieval systems. This paper puts forward an effective solution proposal for the afore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fcaf992487b3e0c3a61867f1f6899c36
https://doi.org/10.21203/rs.3.rs-222235/v1
https://doi.org/10.21203/rs.3.rs-222235/v1
Publikováno v:
2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).
Image enhancement is one of the most important issue of image processing. During acquisition of image, undesirable signals could be added into digital image. Image enhancement algorithms are used to clean the relevant noises. The well-known image fil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83a3ccd12f291b32bc246c6e96669679
https://doi.org/10.1109/ismsit50672.2020.9255100
https://doi.org/10.1109/ismsit50672.2020.9255100
Publikováno v:
2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).
An adaptive Canny edge detector for gray scale images has been presented in this paper. Initially, gradient of gray scale images were obtained by means of Sobel operator and the entropy of gradient images were calculated. Then the gray level, in whic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e02747c7ca3dc817c64dc93bbdea961
https://doi.org/10.1109/ismsit.2019.8932770
https://doi.org/10.1109/ismsit.2019.8932770