Design and synthesis of an image-based object detection system

Abstract

This thesis presents the design and synthesis of an image-based ob-ject detection system, as applied to a facial recognition (FR)-enabled surveillance system. By employing the Design Science Research (DSR) paradigm and following an Action Design Research (ADR) methodology, the real-world problem of synthesizing an FR-enabled surveillance system for the South African environment was investigated. To address this problem, a literature review was done into facial recognition, open-source and commercial facial recognition offerings, systems engineering principles, and the unique constraints of facial recognition in South Africa. An integrated system was designed and synthesized, and tested to ensure that functional requirements were met. A comparative study of one open-source FR engine and one com-mercial FR engine was done, after which a cost-performance evalua-tion model was designed. This was done to compare the two engines, along with a hybrid FR engine that comprises both the open-source and commercial FR engines arranged in series. This model was used to compare the recognition rate to cost of ownership for each of the three FR engines for a range of real-world scenarios. The results from these analyses indicate that there are regions of cost-performance in which each of the FR engines performs best. The most important consideration apart from accuracy is cost, but the em-phasis on performance of the FR engine alone is not always warranted as performance is achieved at a cost. The study therefore provides insight into real-world scenarios encountered in South Africa and thus contributes to the knowledge base on facial recognition systems.