Image Captioning based Smart Navigation System for Visually Impaired

Rane, Chinmayi; Lashkare, Amol; Karande, Aarti M.; Rao, Yunbo

doi:10.1109/iccict50803.2021.9510102

Cited by 11 publications

(1 citation statement)

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“…In contrast, the latter compiles both having adaptive attention systems for caption generation. Rane et al [14] devised a new implementation of smart spectacles related to Optical Character Recognition (OCR) and Image Captioning to ease navigation. The mechanism has a camera that can be entrenched in spectacles, an Image Captioning component, Text-To-Speech (TTS) module, and an OCR module.…”

Section: Related Workmentioning

confidence: 99%

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

Hilal¹,

Alrowais²,

Al‐Wesabi³

et al. 2023

Computer Systems Science and Engineering

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The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing (NLP) and computer vision (CV). It can be driven by applications like image retrieval or indexing, virtual assistants, image understanding, and support of visually impaired people (VIP). Though the VIP uses other senses, touch and hearing, for recognizing objects and events, the quality of life of those persons is lower than the standard level. Automatic Image captioning generates captions that will be read loudly to the VIP, thereby realizing matters happening around them. This article introduces a Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System (RDOAI-ICS) for Visually Impaired People. The presented RDOAI-ICS technique aids in generating image captions for VIPs. The presented RDOAI-ICS technique utilizes a neural architectural search network (NASNet) model to produce image representations. Besides, the RDOAI-ICS technique uses the radial basis function neural network (RBFNN) method to generate a textual description. To enhance the performance of the RDOAI-ICS method, the parameter optimization process takes place using the RDO algorithm for NasNet and the butterfly optimization algorithm (BOA) for the RBFNN model, showing the novelty of the work. The experimental evaluation of the RDOAI-ICS method can be tested using a benchmark dataset. The outcomes show the enhancements of the RDOAI-ICS method over other recent Image captioning approaches.

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Section: Related Workmentioning

confidence: 99%