http://www.iaeme.com/IJEET/index.asp 101 editor@iaeme.com International Journal of Electrical Engineering and Technology (IJEET) Volume 11, Issue 6, August 2020, pp. 101-108, Article ID: IJEET_11_06_010 Available online at http://www.iaeme.com/ijeet/issues.asp?JType=IJEET&VType=11&IType=6 ISSN Print: 0976-6545 and ISSN Online: 0976-6553 DOI: 10.34218/IJEET.11.6.2020.010 © IAEME Publication Scopus Indexed OBJECT DETECTION USING MATLAB, SCILAB AND PYTHON SaiTeja Chopparapu Research Scholar, GITAM- Gandhi Institute of Technology and Management (Deemed to be University) Visakhapatnam, Andhra Pradesh, India Dr. Beatrice Seventline J Professor, GITAM- Gandhi Institute of Technology and Management (Deemed to be University) Visakhapatnam, Andhra Pradesh, India ABSTRACT Classification of images includes assigning an image to a class name, while localization of objects involves drawing a bounding box around one or more objects in the image. Detection of objects is complex and incorporates these two functions, drawing a boundary box around each point of objects in an image and assigning a class name. Both such challenges are commonly referred to as object detection. Object recognition has several uses such as facial tracking, recognition of automobiles, monitoring of people, auto driving cars, surveillance devices etc. This work emphasizes object recognition in image and video for robot operation. The Infrared-Sensor is attached to the Arduino and interfaced with the Scilab for robot movement, and image and video object recognition was also performed using Blob Analysis in the Scilab matlab and python. Key words: Object Recognition, IR Sensor, Blob Analysis, Matlab, Scilab, Python. Cite this Article: SaiTeja Chopparapu and Beatrice Seventline J, Object Detection using Matlab, Scilab and Python. International Journal of Electrical Engineering and Technology, 11(6), 2020, pp. 101-108. http://www.iaeme.com/IJEET/issues.asp?JType=IJEET&VType=11&IType=6 1. INTRODUCTION Object detection is a challenging issue that deals with the detection and location in the image of objects in certain types. Interpreting the position of the subject may be accomplished in various forms, by forming a bounding box around the subject or labeling each pixel in the frame comprising the object (referred to as segmentation). Each object model will have its own particular properties which aid in classifying the subject. Such unique features are used for identification of target type. Different platforms can be used for developing and applying algorithms for object identification and monitoring. They contain Matlab, Scilab, Python etc.