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Articles by Hind Rustum Mohammed
Total Records ( 3 ) for Hind Rustum Mohammed
  Shaymaa Maki Kadham , Hind Rustum Mohammed , Shaymaa Abed Yasseen and Hawraa Saheb Abo Hamed
  It is still a problem how to detection whether digital images are fake or original. In this study, a new algorithm has been developed that uses the properties of the hyper geometric functions to detect fake images from the original image of Mona Lisa by accurately analyzing all the image pixels and expanding the algorithm area by providing an experimental compensation of the x and y values and then reconstructing the regions and components and matching it to the original image. Statistical support for digital counterfeit image detection. The database used consisted of 15 fake images and the original image and the algorithm proved its efficiency accurately in detecting the forgery.
  Hassan Mohammed Mahdi Al-Jawahry and Hind Rustum Mohammed
  Image classification is important in several fields which depend on the methods of extracting the features. This study proposes a new method for features extraction called Local Quadrant Pattern with Co-occurrence Matrix (LQP-CM) that related with Local Ternary Pattern (LTP) and Gray-Level Co-occurrence Matrix (GLCM). LQP-CM will map the values into four types instead of two like Local Binary Pattern (LBP) or three like LTP. For classification, this study will use the Euclidean Distance (ED) to classifying the features that extracting. The data set that used in this study is Brodatz dataset. The MATLAB environment was adopted in the programming and the criteria was used to evaluate the performance of the proposed method is percentage of correct classification which proved successful in classification the database used in high efficiency.
  Noor Riyadh Kareem and Hind Rustum Mohammed
  In this research, a new method for deleting objects for colour images based on fuzzy sets are presented. The idea of filtering is that the fuzzy set filter to remove objects. The results show that the proposed filter is more efficient than other methods. MATLAB would be the paper environment (data set are 30 colour images with any format). Performance criteria used to demonstrate the accuracy of the method used and its best statistical criteria such as (mean and peak signal to noise ratio).
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