COMPUTER VISION BASED ON RASPBERRY PI SYSTEM
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Issue Vol. 16 No. 4 (2020)
-
GRAPH-BASED FOG COMPUTING NETWORK MODEL
5-20
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JOINT EFFECT OF FORECASTING AND LOT-SIZING METHOD ON COST MINIMIZATION OBJECTIVE OF A MANUFACTURER: A CASE STUDY
21-36
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ELECTROCARDIOGRAM GENERATION SOFTWARE FOR TESTING OF PARAMETER EXTRACTION ALGORITHMS
37-47
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ARCHITECTURAL PARADIGM OF THE INTERACTIVE INTERFACE MODULE IN THE CLOUD TECHNOLOGY MODEL
48-55
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CLASSIFICATION OF EEG SIGNAL BY METHODS OF MACHINE LEARNING
56-63
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DEVELOPMENT OF AN ONTOLOGY-BASED ADAPTIVE PERSONALIZED E-LEARNING SYSTEM
64-84
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COMPUTER VISION BASED ON RASPBERRY PI SYSTEM
85-102
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ORDER VIOLATION IN MULTITHREADED APPLICATIONS AND ITS DETECTION IN STATIC CODE ANALYSIS PROCESS
103-117
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Abstract
The paper focused on designing and developing a Raspberry Pi based system employing a camera which is able to detect and count objects within a target area. Python was the programming language of choice for this work. This is because it is a very powerful language, and it is compatible with the Pi. Besides, it lends itself to rapid application development and there are online communities that program Raspberry Pi computer using python. The results show that the implemented system was able to detect different kinds of objects in a given image. The number of objects were also generated displayed by the system. Also the results show an average efficiency of 90.206% was determined. The system is therefore seen to be highly reliable.
