Smart Assistive System for Visually Impaired People Obstruction Avoidance Through Object Detection and Classification

Masud, Usman; Saeed, Tareq; Malaikah, Hunida; Islam, Fezan ul; Abbas, Ghulam

doi:10.1109/access.2022.3146320

Cited by 52 publications

(10 citation statements)

References 37 publications

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“…As a result, a method needs to reduce speckles ultimately and effectively preserve the edges and retain fine superior points in the image. The Viola-Jones technique is a method described in [28][29][30] for detection purposes, as the detection framework checks for features such as the total of image pixels within rectangular sections. It is highly sophisticated because it involves well over one rectangle characteristic within the approach, although it is simple to apply with a limited dataset.…”

Section: Theoretical Backgroundsmentioning

confidence: 99%

Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

Manikandan¹,

Karthikeyan²,

Babu³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Signal to noise ratio in ultrasound medical images captured through the digital camera is poorer, resulting in an inaccurate diagnosis. As a result, it needs an efficient despeckling method for ultrasound images in clinical practice and telemedicine. This article proposes a novel adaptive fuzzy filter based on the directionality and translation invariant property of the Non-Sub sampled Contour-let Transform (NSCT). Since speckle-noise causes fuzziness in ultrasound images, fuzzy logic may be a straightforward technique to derive the output from the noisy images. This filtering method comprises detection and filtering stages. First, image regions classify at the detection stage by applying fuzzy inference to the directional difference obtained from the NSCT noisy image. Then, the system adaptively selects the better-suited filter for the specific image region, resulting in significant speckle noise suppression and retention of detailed features. The suggested approach uses a weighted average filter to distinguish between noise and edges at the filtering stage. In addition, we apply a structural similarity measure as a tuning parameter depending on the kind of noise in the ultrasound pictures. The proposed methodology shows that the proposed fuzzy adaptive filter effectively suppresses speckle noise while preserving edges and image detailed structures compared to existing approaches.

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Section: Theoretical Backgroundsmentioning

confidence: 99%

Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

Manikandan¹,

Karthikeyan²,

Babu³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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show abstract

“…In order to improve the detection speed, 1-stage detector that integrates the region proposal and classification steps have been proposed. The representative technologies are YOLO [20], SSD [21], and Retina-Net [22], and they are widely used in real-time applications such as a biomedical service [23] and assistive system for visually impaired people [24].…”

Section: Object Detectionmentioning

confidence: 99%

Effective Denoising Architecture for Handling Multiple Noises

Kim¹,

Kim²

2023

Computer Systems Science and Engineering

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Object detection, one of the core research topics in computer vision, is extensively used in various industrial activities. Although there have been many studies of daytime images where objects can be easily detected, there is relatively little research on nighttime images. In the case of nighttime, various types of noises, such as darkness, haze, and light blur, deteriorate image quality. Thus, an appropriate process for removing noise must precede to improve object detection performance. Although there are many studies on removing individual noise, only a few studies handle multiple noises simultaneously. In this paper, we propose a convolutional denoising autoencoder (CDAE)-based architecture trained on various types of noises. We also present various composing modules for each noise to improve object detection performance for night images. Using the exclusively dark (ExDark) Image dataset, experimental results show that the Sequential filtering architecture showed superior mean average precision(mAP) compared to other architectures.

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“…Their smart cane can guide the user by vibrating to avoid aerial obstacles and collision accidents and promptly notify the user's family when he or she falls. Masud et al [31] propose a smart cane consisting of a Raspberry-Pi 4B, an RGB-D Camera, and an ultrasonic Sensor. Their smart cane can recognize obstacles by simple calculations and provides hints by vibration.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Sensory Guidance System for the Visually Impaired Using YOLO and ORB-SLAM

Xie

Zhang

et al. 2022

Information

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Guidance systems for visually impaired persons have become a popular topic in recent years. Existing guidance systems on the market typically utilize auxiliary tools and methods such as GPS, UWB, or a simple white cane that exploits the user’s single tactile or auditory sense. These guidance methodologies can be inadequate in a complex indoor environment. This paper proposes a multi-sensory guidance system for the visually impaired that can provide tactile and auditory advice using ORB-SLAM and YOLO techniques. Based on an RGB-D camera, the local obstacle avoidance system is realized at the tactile level through point cloud filtering that can inform the user via a vibrating motor. Our proposed method can generate a dense navigation map to implement global obstacle avoidance and path planning for the user through the coordinate transformation. Real-time target detection and a voice-prompt system based on YOLO are also incorporated at the auditory level. We implemented the proposed system as a smart cane. Experiments are performed using four different test scenarios. Experimental results demonstrate that the impediments in the walking path can be reliably located and classified in real-time. Our proposed system can function as a capable auxiliary to help visually impaired people navigate securely by integrating YOLO with ORB-SLAM.

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Smart Assistive System for Visually Impaired People Obstruction Avoidance Through Object Detection and Classification

Cited by 52 publications

References 37 publications

Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

Effective Denoising Architecture for Handling Multiple Noises

A Multi-Sensory Guidance System for the Visually Impaired Using YOLO and ORB-SLAM

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