Sign Language Recognition has emerged as one of the important area of research in Computer Vision. The difficulty faced by the researchers is that the instances of signs vary with both motion and appearance. Thus, in this paper a novel approach for recognizing various alphabets of Indian Sign Language is proposed where continuous video sequences of the signs have been considered. The proposed system comprises of three stages: Preprocessing stage, Feature Extraction and Classification. Preprocessing stage includes skin filtering, histogram matching. Eigen values and Eigen Vectors were considered for feature extraction stage and finally Eigen value weighted Euclidean distance is used to recognize the sign. It deals with bare hands, thus allowing the user to interact with the system in natural way. We have considered 24 different alphabets in the video sequences and attained a success rate of 96.25%.
Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Extraction and Classification. Twenty four signs were considered in this paper, each having ten samples, thus a total of two hundred forty images was considered for which recognition rate obtained was 97 pe…
MCKV Institute of Engineering（MCKV工程学院）；Jadavpur University（贾达普大学）
Automatic License Plate Recognition (ALPR) is a challenging area of research due to its importance to variety of commercial applications. The overall problem may be subdivided into two key modules, firstly, localization of license plates from vehicle images, and secondly, optical character recognition of extracted license plates. In the current work, we have concentrated on the first part of the problem, i.e., localization of license plate regions from Indian commercial vehicles as a significant step towards development of a complete ALPR system for Indian vehicles. The technique is based on c…
Indian Licence Plate Detection is a problem that has not been explored much at an open-source level.There are proprietary solutions available for it, but there is no big open-source dataset that can be used to perform experiments and test different approaches.Most of the large datasets available are for countries like China, Brazil, but the model trained on these datasets does not perform well on Indian plates because the font styles and plate designs used vary significantly from country to country.This paper introduces an Indian license plate dataset with 16192 images and 21683 plate plates a…
In this paper, the task of recognizing signs made by hearing impaired people at sentence level has been addressed. A novel method of extracting spatial features to capture hand movements of a signer has been proposed. Frames of a given video of a sign are preprocessed to extract face and hand components of a signer. The local centroids of the extracted components along with the global centroid are exploited to extract spatial features. The concept of interval valued type symbolic data has been explored to capture variations in the same sign made by the different signers at different instances …
Due to the COVID-19 pandemic, wearing face masks has become a mandate in public places worldwide. Face masks occlude a significant portion of the facial region. Additionally, people wear different types of masks, from simple ones to ones with graphics and prints. These pose new challenges to face recognition algorithms. Researchers have recently proposed a few masked face datasets for designing algorithms to overcome the challenges of masked face recognition. However, existing datasets lack the cultural diversity and collection in the unrestricted settings. Country like India with attire diver…
Indian Institute of Technology, Kharagpur（印度理工学院卡拉格普尔分校）
Automatic recognition of spontaneous facial expressions is a major challenge in the field of affective computing. Head rotation, face pose, illumination variation, occlusion etc. are the attributes that increase the complexity of recognition of spontaneous expressions in practical applications. Effective recognition of expressions depends significantly on the quality of the database used. Most well-known facial expression databases consist of posed expressions. However, currently there is a huge demand for spontaneous expression databases for the pragmatic implementation of the facial expressi…
Generation of Indian Sign Language Letters, Numbers, and Words
Electrical Communication Engineering Indian Institute of Science, Banglore Bengaluru, India（电子通信工程 印度科学研究院，班加罗尔 印度班加罗尔）；Automation Indian Institute of Science, Banglore Bengaluru, India（自动化 印度科学研究院，班加罗尔 印度班加罗尔）；Electrical Engineering Indian Institute of Science, Banglore Bengaluru, India（电气工程 印度科学研究院，班加罗尔 印度班加罗尔）
K. J. Somaiya College of Engineering（K. J. 索马亚工程学院）；University of Mumbai（孟买大学）
This paper presents a system which can recognise hand poses & gestures from the Indian Sign Language (ISL) in real-time using grid-based features. This system attempts to bridge the communication gap between the hearing and speech impaired and the rest of the society. The existing solutions either provide relatively low accuracy or do not work in real-time. This system provides good results on both the parameters. It can identify 33 hand poses and some gestures from the ISL. Sign Language is captured from a smartphone camera and its frames are transmitted to a remote server for processing. The…
AI technologies for Natural Languages have made tremendous progress recently. However, commensurate progress has not been made on Sign Languages, in particular, in recognizing signs as individual words or as complete sentences. We introduce OpenHands, a library where we take four key ideas from the NLP community for low-resource languages and apply them to sign languages for word-level recognition. First, we propose using pose extracted through pretrained models as the standard modality of data to reduce training time and enable efficient inference, and we release standardized pose datasets fo…
