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Block diagram of book reader with Raspberry Pi
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This paper presents the automatic document reader for visually impaired people, developed on Raspberry Pi. It uses the Optical character recognition technology for the identification of the printed characters using image sensing devices and computer programming. It converts images of typed, handwritten, or printed text into machine encoded text. In...
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Context 1
... project can also be implemented for the automatic detection of road signs, warning signs, in other terms to improve the blind navigation on larger scale. Figure 1 shows the block diagram of the proposed book reader. In this system, the printed text is to be placed under the camera view by the blind person to ensure the image of good quality and fewer distortions. ...
Context 2
... project can also be implemented for the automatic detection of road signs, warning signs, in other terms to improve the blind navigation on larger scale. Figure 1 shows the block diagram of the proposed book reader. In this system, the printed text is to be placed under the camera view by the blind person to ensure the image of good quality and fewer distortions. ...
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Citations
... Raspberry Pi [31], [32] The Raspberry Pi is the project's major implementation goal since it acts as a bridge between the camera, sensors, and image processing results, as well as giving functions to change peripheral equipment. (Keyboard and USB) ...
p class="p1">Shopping of day-to-day items and keeping track of the shopping list can be a tedious and a time-consuming procedure, especially if it has to be done frequently. mySmartCart is a mobile application design proposed to transform the traditional way of writing a shopping list to a digitalized smart list which implements voice recognition and handwriting recognition for processing the natural language input of the user. The system design comprises four modules: i) input- which takes voice and handwritten list image input from the user; ii) processing- natural language processing of input data and converted to digital shopping list; iii) classification - list items classified into respective categories using machine learning algorithms; iv) output - searching on e-commerce applications and adding to shopping cart. The design proposed utilizes natural languages to communicate with the user thus enhancing their shopping experience. Google cloud speech recognition and tesseract optical character recognition (OCR) for natural language processing have been utilized in the prototype along with Support Vector Machine classifier for categorization.</p
... The text from the input image was retrieved using the OCR algorithm by the system, and the text was then spoken out using the Text-to-Speech algorithm. There are three basic steps in the audio reading system: the input step to capture an image, the processing step to apply the OCR algorithm, and the output step to convert extracted text into the corresponding voice [1] [2]. ...
Many systems are available to help the blind person in his life. This paper aims to prove the specific proposed audio reading, meaning, and recommendation system are efficient and real-time for the blind person. These systems are tested and discussed from the aspects of real-time, efficiency, accuracy, and reliability. The dataset is images with different text font sizes and views which is used in testing these three systems.
... In addition to reading aloud, this prototype also determines how much space is ahead of the user [3] [4]. Finally, eliminating the need for blind shoppers' help and providing them with a welcoming, luxurious shopping experience are the highest priorities [5]. Think about learning to read instead of using Braille. ...
In certain cases, persons with disabilities may be forced to rely on others for the performance of their duties. Blindness is one of the impairments that might be encountered. Up to this point, there has been N number of solutions presented that make life easier for visually impaired individuals. One of the problems they face on a daily basis is making an independent purchase of a product they need. To solve this issue, the approach is to utilize a camera to record a picture, which is then processed using the tesseract method to extract text from the image, which is then transformed into an audio file that can be heard using headphones. Following the implementation of this strategy, during this shopping trolley technology to detect the item put with machine learning and precision location discover a person will be used to locate a person in the shopping trolley.
... Audio Reading System consists of three general steps: Firstly, capture image for text want to read it using a camera, then sent it to the processing step. Secondly, processing step where text will be filtered and will be extracted by Optical Character Recognition (OCR) algorithm, and finally, output step used the Text-to-Speech algorithm to convert text into corresponding voice using speaker device [1] [2]. Optical Character Recognition (OCR) is one of the important functions that convert the written text or printed text to the editable text. ...
... In another word, translation of the character image into character codes, such as ASCII. There are many application of OCR algorithm such as Text-to-Speech, machine learning, and translation [2]. Recent developments in computer systems, camera, and different software such as python language make it easy build audio reading system. ...
... Also this paper propose an effective motion-based method to define a region of interest (ROI) in the image. In Anush Goel and et al [2] (2018) automatic document reader for visually impaired people have been presents in this paper based on the Raspberry Pi. It uses the OCR algorithm for the identification of the printed characters using camera devices and computer programming. ...
Audio Reading System is used to help blind people to read the text based on camera as input device and speaker as output device. The system used the OCR algorithm to extract the text from input image and Text-to-Speech algorithm to convert text into corresponding voice. In this paper, we review newest research of audio reading system. We discuss the hardware and software which is used on system for different types approach. Finally, the result of this paper that is: Raspberry pi, python and tesseract are best tools used in Audio reading system. Also the braille and finger print devices are not efficient and not easy to use.
... First step, capture image for text want to read it using a camera, then sent it to the processing step. Second step, image processing where text will be filtered and will be extracted by Optical Character Recognition (OCR) algorithm, and finally, output step used the Text-to-Speech algorithm to speak the text using speaker device (Shirke & Patil, 2018) (Goel et al., 2018). ...
According to the World Health Organization there are approximately 285 million blind people around the world. These people are faced challenges when reading a book. This paper aims to design and implementation new real time mobile cloud audio reading system for blind persons. The proposed methodology consists of following steps: In Client Side, firstly, capture image of text by camera. Secondly, check the page localization. Thirdly, send image to server. In Cloud Side (Server Side), firstly, apply the modify EAST algorithm on received image to text detection. Secondly, apply OCR algorithm to extract text from image. Thirdly, apply post-processing step to correct the in corrected text. Finally, return text to client side to speak it using text-to-speech algorithm.
... A. Goel et al. [17] implemented a system for English book readers in Raspberry Pi. Here python programming is used for text extraction from captured images and audio speech conversion. ...
... A. Goel et al. [17] implemented a system for English book readers in Raspberry Pi. Here python programming is used for text extraction from captured images and audio speech conversion. ...
Optical Character Recognition (OCR) technology is very helpful for visually impaired or illiterate persons who are unable to read text documents but need to reach the content of the text documents. In this paper, a camera-based assistive device is used that can be applied for visually impaired or illiterate people to understand Bangla text documents by listening to the contents of the Bangla text images. This work mainly involves the extraction of the Bangla text from the Bangla text image and converts the extracted text to speech. This work has been fulfilled with Raspberry Pi and a camera module by applying the concepts of the Tesseract OCR engine, the Open Source Computer Vision, and the Google Speech Application Program Interface. This work can help people speaking Bangla language who are unable to read or have a significant loss of visual sight.
... In literature, many systems employ the concept of OCR for image capturing and text to speech synthesis for its conversion in voice signals. Goel et al. [2] proposed in their paper to develop the system assistive reading system for visually impaired people by implementing OCR through the tesseract library and OpenCV for the detection of text. For conversion into the voice signals, they proposed a text to speech module in their research paper. ...
There are millions of visually impaired people in the world. According to the World Health Organization (WHO) data on visual impairment, 1.3 billion people are living with some kind of visual impairment while 36 million people are completely visually impaired. Reading is one of the major necessities of visually impaired people. Numerous researchers have worked on developing a mechanism that allows blind people to detect obstacles, to read the labels or specific currencies and to read the written, typed or printed text. We proposed a system which facilitates the visually impaired people by converting the text into voice signal based on raspberry pi. Optical Character Recognition (OCR) scheme is employed for the detection of printed text using a camera. Typed, handwritten characters or text are converted into machine-encoded text. The proposed method is developed on the raspberry pi in which OCR is employed for an image to audio converter which is the output of the system. It is a smart real-time device based on OCR.
... The major factors needed are depth information and image intensities. [2] In this paper, the obstacles are identified using electronic travel aids; it also helps by providing other services and also used to get information from the surroundings. In this system, a user gets the data's about the obstacles in the current environment using haptic device. ...
Visual impairment persons are not able to do all works as normal persons especially during purchasing products in supermarket. To help the blind peoples recognise the objects a text reading method is proposed along with the help of camera. A motion detection method is used to detect the presence of the object. The audio instructions about all the objects and their location in supermarket are notified to the blind user that helps them to move freely inside the supermarket. The proposed system aims to make more convenient for the blind persons to purchase in a sophisticated environment. This system also provides easy shopping, consumers time is saved, etc. The implementation of proposed system is done using artificial intelligence and OCR technology. General Terms Visually impaired people, smart shopping, OCR.
The development of an image-to-audio conversion system represents a significant stride towards enhancing accessibility and autonomy for visually impaired individuals. This innovative technology leverages computer vision and audio synthesis techniques to convert visual information from images into auditory cues, enabling blind users to interpret and comprehend their surroundings more effectively. The core of this system relies on advanced computer vision algorithms that process input images, recognizing objects, text, and scene elements. These algorithms employ deep learning models to extract meaningful visual features and convert them into a structured representation of the image content. Simultaneously, natural language processing techniques are employed to extract and interpret textual information within the image, such as signs, labels, or written instructions. Once the image content is comprehended, an audio synthesis engine generates a corresponding auditory output. This auditory output is designed to convey the information in a clear and intuitive manner. Additionally, the system can adapt its output based on user preferences and environmental context, providing a customizable and dynamic auditory experience. It empowers blind individuals to independently access visual information from a variety of sources, including printed materials, digital displays, and real-world scenes. Moreover, it promotes inclusion by reducing the reliance on sighted assistance and fostering greater self-reliance and confidence among visually impaired individuals. By harnessing computer vision and audio synthesis, it provides a means for blind individuals to access and interpret visual information independently, thereby enhancing their autonomy, inclusion, and overall quality of life. This innovative solution underscores the potential of technology to bridge accessibility gaps and empower individuals with disabilities.
