© 2018, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2018/v5/i2/v5i207 50 International Journal of Computer Engineering in Research Trends Multidisciplinary, Open Access, Peer-Reviewed and fully refereed Research Paper Volume-5, Issue-2 ,2018 Regular Edition E-ISSN: 2349-7084 Evaluation of Industrial Based Object Detection Method Using Artificial Neural Network F. S. Ishaq 1* , I. A. Alhaji 2 , Halis Altun 3 , Y. Atomsa 4 , M. L. Jibrin 5 , S. A. Sani 6 1* Dept. of Mathematics and Computer Science, Faculty of Science, Federal University, Kashere, Gombe, Nigeria 2 Dept. of Physics, Faculty of Science, Federal University, Kashere, Gombe, Nigeria 3 Dept. of Computer Engineering, Faculty of Engineering, Karatay University, Konya, Turkey 4 Dept. of Mathematics and Computer Science, Faculty of Science, Federal University, Kashere, Gombe, Nigeria 5 Dept. of Mathematics and Computer Science, Faculty of Science, Federal University, Kashere, Gombe, Nigeria 6 ICT Directorate, Federal University, Kashere, Gombe, Nigeria F. S. Ishaq _ faisalsishaq@gmail.com, I. A. Alhaji _ alhaji259@gmail.com, Y. Atomsa _ au.nlaro@gmail.com, M. L. Jibrin_mljtech@gmail.com, S. A. Sani _ aminushafiu@yahoo.com *Corresponding Author: F. S. Ishaq1_ faisalsishaq@gmail.com Available online at: http://www.ijcert.org Received: 18/February/2017, Revised: 19/February/2017, Accepted: 23/February/2017, Published: 27/February/2017 Abstract:- The essence of the study is to analyse an algorithm which will provide a robust and computationally light method, which might be suitable to implement in the real-time industrial application such as object detection and recognition. For industrial applications, the primary step in automatic detection and classification of an object is to find the object automatically from an image using features related to its shape. This chore is a very complex one. Therefore, to hit the target Histogram of oriented gradient (HOG) algorithm is selected to extract the image features. Average Magnitude Difference Function AMDF is employed to correct the alignment defect. Finally, Artificial Neural Network (ANN) was employed to detect the type of object in the image efficiently. None the less, a database was generated. The database consists of images of real industrial products which are of different shapes and sizes, captured under different lightning conditions. The outcome of the experiment conducted on the database recorded 98.10% success. Keywords: 1-D mask, HOG algorithm, AMDF algorithm, k-nearest Neighbours algorithm, Cross-correlation Functions algorithms and MLP algorithm 1. Introduction For industrial applications, the primary step in automatic detection and classification of an object is to find the object automatically from an image using features related to its shape. Therefore shape detection plays an important role and has an intensive usage in various applications [1] such as in robotics; object classification is needed to recognize a certain object in a cluttered scene [2]. In the industries detecting objects With computers is difficult. This is as a result of some Complications such as Initially, products from industries vary in many forms such as type, size and Shape. Hence, using object detection system in the industries is only possible if the algorithm is robust enough to eliminate these variations. Subsequently, the industrial operation involves moving objects from one place to the other; this might result in objects being placed in different poses. The methods used needs to distinguish the objects with different orientations accurately. Thirdly, the illumination in the environment varies due to, shadows of other machine or humans. Therefore the