Design thinking, having applications in many fields, is emerging to be a pragmatic technique for facilitating Human Centred Design (HCD), a modern-day necessity, through a well-defined systematic process. This paper presents a case study detailing the application of design thinking principles to approach and develop solutions for the visually challenged to recognize the denomination of Indian currencies. Throughout the paper, specific implementations of design thinking principles have been detailed with emphasis on the key takeaways from the various stages. A comprehensive review of our approach compared to existing and unconventional applications has been provided to underline the importance of incorporating design thinking into emergent consumer-oriented solutions. A lot of research has been done in developing denomination classification models, however, there seems to be a lack of solutions designed through the perspective of a blind person who plays the critical factor in determining effectiveness once deployed. The design procedure helped us realize the importance of developing a simple user-friendly interface with a single input button and audio relays to guide the blind user during operation. Establishing a good platform for interaction and feedback was found to be critical in helping us modify and prioritize aspects such as achieving a low false-positive percentage and the addition of a high threshold Softmax function which made the solution design effective.
Manually processing invoices which are in the form of scanned photocopies is a time-consuming process. There is a need to automate the task of extraction of data from the invoices with a similar format. In this paper we investigate and analyse various techniques of image processing and text extraction to improve the results of the optical character recognition (OCR) engine, which is applied to extract the text from the invoice. This paper also proposes the design and implementation of a web enabled invoice processing system (IPS). The IPS consists of an annotation tool and an extraction tool. The annotation tool is used to mark the fields of interest in the invoice which are to be extracted. The extraction tool makes use of opensource computer vision library (OpenCV) algorithms to detect text. The proposed system was tested on more than 25 types of invoices with the average accuracy score lying between 85% and 95%. Finally, to provide ease of use, a web application is developed which also presents the results in a structured format. The entire system is designed so as to provide flexibility and automate the process of extracting details of interest from the invoices.
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