Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : GLCM

Using Texture Feature in Fruit Classification

Mauj H. Abd al karim; Abdulamir A. Karim

Engineering and Technology Journal, 2021, Volume 39, Issue 1B, Pages 67-79
DOI: 10.30684/etj.v39i1B.1741

Recent advances in computer vision have allowed wide-ranging applications in every area of life. One such area of application is the classification of fresh products, but the classification of fruits and vegetables has proven to be a complex problem and needs further development. In recent years, various machine learning techniques have been exploited with many methods of describing the different features of fruit and vegetable classification in many real-life applications. Classification of fruits and vegetables presents significant challenges due to similarities between layers and irregular characteristics within the class.Hence , in this work, three feature extractor/ descriptor which are local binary pattern (LBP), gray level co-occurrence matrix (GLCM) and, histogram of oriented gradient(HoG) has been proposed to extract fruite features , the extracted features have been saved in three feature vectors , then desicion tree classifier has been proposed to classify the fruit types. fruits 360 datasets is used in this work, where 70% of the dataset were used in the training phase while 30% of it used in the testing phase. The three proposed feature extruction methods plus the tree classifier have been used to classifying fruits 360 images, results show that the the three feature extraction methods give a promising results , while the HoG method yielded a poerfull results in which the accuracy obtained is 96%.

Biometric Privacy Using Secret Image Sharing

A.T. Hashim; D.A. Noori

Engineering and Technology Journal, 2017, Volume 35, Issue 7, Pages 701-708

Biometric technique includes uniquely identifying person based on their physical or behavioral characteristics. It is mainly used for authentication. Iris scanning is one of the most secure techniques among all biometrics because of its uniqueness and stability (i.e., no two persons in the world can have same iris). For authentication, the feature template in the database and the user template should be the same method for extracting iris template in this proposed system. Also storing the template in the database securely is not a secure approach, because it can be stolen or tampered. To deal with this security issue, the proposed system is securely storing the template in the database by firstly using randomness to scramble the bits of template based on chaos system. Secondly, a hiding technique is utilized to hide the scrambled templates in host images randomly. Finally, a secret sharing based on linear system is implemented on the iris template in database to protect it and adding extra layer of iris authentication system. The proposed secret sharing system has been generated a meaningful shares which overcomes the problem in traditional methods. Also in proposed system, two approaches of iris extraction have been presented.