Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking
المؤلفون المشاركون
Ben Abdelali, Abdessalem
Mtibaa, Abdellatif
Bourennane, El-Bay
Hajjaji, Mohamed Ali
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-04-07
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
This paper presents a novel watermarking method, applied to the medical imaging domain, used to embed the patient’s data into the corresponding image or set of images used for the diagnosis.
The main objective behind the proposed technique is to perform the watermarking of the medical images in such a way that the three main attributes of the hidden information (i.e., imperceptibility, robustness, and integration rate) can be jointly ameliorated as much as possible.
These attributes determine the effectiveness of the watermark, resistance to external attacks, and increase the integration rate.
In order to improve the robustness, a combination of the characteristics of Discrete Wavelet and Karhunen Loeve Transforms is proposed.
The Karhunen Loeve Transform is applied on the subblocks (sized 8×8) of the different wavelet coefficients (in the HL2, LH2, and HH2 subbands).
In this manner, the watermark will be adapted according to the energy values of each of the Karhunen Loeve components, with the aim of ensuring a better watermark extraction under various types of attacks.
For the correct identification of inserted data, the use of an Errors Correcting Code (ECC) mechanism is required for the check and, if possible, the correction of errors introduced into the inserted data.
Concerning the enhancement of the imperceptibility factor, the main goal is to determine the optimal value of the visibility factor, which depends on several parameters of the DWT and the KLT transforms.
As a first step, a Fuzzy Inference System (FIS) has been set up and then applied to determine an initial visibility factor value.
Several features extracted from the Cooccurrence matrix are used as an input to the FIS and used to determine an initial visibility factor for each block; these values are subsequently reweighted in function of the eigenvalues extracted from each subblock.
Regarding the integration rate, the previous works insert one bit per coefficient.
In our proposal, the integration of the data to be hidden is 3 bits per coefficient so that we increase the integration rate by a factor of magnitude 3.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hajjaji, Mohamed Ali& Bourennane, El-Bay& Ben Abdelali, Abdessalem& Mtibaa, Abdellatif. 2014. Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking. BioMed Research International،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-462622
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hajjaji, Mohamed Ali…[et al.]. Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking. BioMed Research International No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-462622
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hajjaji, Mohamed Ali& Bourennane, El-Bay& Ben Abdelali, Abdessalem& Mtibaa, Abdellatif. Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-462622
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-462622
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر