Inproceedings
عنوان الكتاب :
1st International Conference on New Technologies of Information and Communication (NTIC'15)
المكان :
Mila, Algeria
ISBN : 978-1-4673-6684-7
الناشر :
معلومات
الفترة : November 2015
الصفحات : 1-6
التفاصيل
Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study
Similarity measures play crucial role in Content-Based Dermoscopic Image Retrieval (CBDIR). This paper analyses and compares images based respectively on twelve distances namely: Minkowski, Euclidean, Standardized Euclidean, Mahalanobis, Manhattan, Chebychev, Cosine, Canberra, Relative Deviation, Bray-Curtis, Square Chord and Square Chi-Squared measures for CBDIR. Two dermatologists were asked to diagnose 176 skin lesion images in order to classify them. Eight common classes of pigmented skin lesions have been identified, including: Melanoma, Nevus/Mole (ML), Lentigo (Len), Basal Cell Carcinoma (BCC), Seborrhoeic Keratosis (SK), Actinic Keratosis (AK), Angioma (AG) and Dermatofibroma (DF). Color and texture features have been extracted from the segmented skin lesions. Then a series of CBDIR experiments were conducted on the image database. The results indicate that the CBDIR performance is significantly improved by using Canberra and Bray-Curtis distances compared to conventional measures.
الكلمات المفتاحية :
Content-based retrieval Image classification Image colour analysis Image retrieval Image segmentation Image texture Medical image processing
مرجع الإقتباس :
misc-lab-239
DOI :
10.1109/NTIC.2015.7368761
الرابط :
Texte intégral
ACM :
K. Belattar and S. Mostefai. 2015. Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study. In Proceedings of the 1st International Conference on New Technologies of Information and Communication (NTIC'15), Mila, Algeria (November 2015), IEEE, 1-6. DOI: https://doi.org/10.1109/NTIC.2015.7368761.
APA :
Belattar, K. & Mostefai, S. (2015, November). Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study. In Proceedings of the 1st International Conference on New Technologies of Information and Communication (NTIC'15), Mila, Algeria, IEEE, 1-6. DOI: https://doi.org/10.1109/NTIC.2015.7368761
IEEE :
K. Belattar and S. Mostefai, "Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study". In Proceedings of the 1st International Conference on New Technologies of Information and Communication (NTIC'15), Mila, Algeria, IEEE, pp. 1-6, November, 2015. DOI: https://doi.org/10.1109/NTIC.2015.7368761.
BibTeX :
@inproceedings{misc-lab-239,
author = {Belattar, Khadidja and Mostefai, Sihem},
title = {Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study},
booktitle = {1st International Conference on New Technologies of Information and Communication (NTIC'15)},
location = {Mila, Algeria},
isbn = {978-1-4673-6684-7},
pages = {1--6},
publisher = {IEEE},
year = {2015},
month = {November},
doi = {10.1109/NTIC.2015.7368761},
url = {https://ieeexplore.ieee.org/abstract/document/7368761},
keywords = {content-based retrieval, image classification, image colour analysis, image retrieval, image segmentation, image texture, medical image processing}
}
RIS :
TY  - CONF
TI - Similarity measures for Content-Based Dermoscopic Image Retrieval: A comparative study
AU - K. Belattar
AU - S. Mostefai
PY - 2015
BT - 1st International Conference on New Technologies of Information and Communication (NTIC'15), Mila, Algeria
SN - 978-1-4673-6684-7
SP - 1
EP - 6
PB - IEEE
AB - Similarity measures play crucial role in Content-Based Dermoscopic Image Retrieval (CBDIR). This paper analyses and compares images based respectively on twelve distances namely: Minkowski, Euclidean, Standardized Euclidean, Mahalanobis, Manhattan, Chebychev, Cosine, Canberra, Relative Deviation, Bray-Curtis, Square Chord and Square Chi-Squared measures for CBDIR. Two dermatologists were asked to diagnose 176 skin lesion images in order to classify them. Eight common classes of pigmented skin lesions have been identified, including: Melanoma, Nevus/Mole (ML), Lentigo (Len), Basal Cell Carcinoma (BCC), Seborrhoeic Keratosis (SK), Actinic Keratosis (AK), Angioma (AG) and Dermatofibroma (DF). Color and texture features have been extracted from the segmented skin lesions. Then a series of CBDIR experiments were conducted on the image database. The results indicate that the CBDIR performance is significantly improved by using Canberra and Bray-Curtis distances compared to conventional measures.
KW - content-based retrieval
KW - image classification
KW - image colour analysis
KW - image retrieval
KW - image segmentation
KW - image texture
KW - medical image processing
DO - 10.1109/NTIC.2015.7368761
UR - https://ieeexplore.ieee.org/abstract/document/7368761
ID - misc-lab-239
ER -