Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : LBP

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%.

Real Time Face Recognition in Video Using Linear Discriminate Analysis and Local Binary Patterns

Yossra Hussain Ali; Istabraq Saleem Abed Aljabar

Engineering and Technology Journal, 2015, Volume 33, Issue 4, Pages 690-701

The need for robust recognition system in applications of surveillance and biometrics is increasing with the advancements in technology. The conventional method of passwords and pin numbers can be easily hacked,a so these are being rapidly replaced by more secure and reliable biometric methods. This paper produces a new real-time surveillance system in video which makes use of face characteristics of the user for correct identification. The face is first detected using Viola-Jones algorithm, then a hybrid algorithms were used to extract the features and determine the faces linear discriminate analysis and local binary patterns.The proposed approach tested and gives efficient results when compared with other previous approach.