—Multispectral imaging is widely used in remote sensing applications from UAVs and ground-based p... more —Multispectral imaging is widely used in remote sensing applications from UAVs and ground-based platforms. Multispectral cameras often use a physically different camera for each wavelength causing misalignment in the images for different imaging bands. This misalignment must be corrected prior to concurrent multi-band image analysis. The traditional approach for multispectral image registration process is to select a target channel and register all other image channels to the target. There is no objective evidence-based method to select a target. The possibility of registration to some intermediate channel to the target is not usually considered, but could be beneficial if there is no target channel for which direct registration performs well for every other channel. In this paper, we propose an automatic data-driven multispectral image registration framework that determines a target channel, and possible intermediate registration steps based on the assumptions that 1) some reasonable minimum number of control points correspondences between two channels is needed to ensure a low-error registration; and 2) a greater number of such correspondences generally results in lower registration error. Our prototype is tested on three multispectral datasets captured with UAV-mounted multispectral cameras. The resulting registration schemes had more control point correspondences on average than the traditional register-all-to-one-target-channel approach in all of our experiments. For most channels in our three datasets, our registration schemes produced lower back-projection error than the direct-to-target-channel based registration approach.
Skin diseases are among the most common health
problems worldwide. In this article we proposed a ... more Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.
ICCIT-Workshop on Human And Technology (ICCIT-WHAT 2013), Mar 10, 2014
We have presented our work Beetle designed to support farmers in rural area to detect crop diseas... more We have presented our work Beetle designed to support farmers in rural area to detect crop disease. The
system shows promises in terms of disease detection. We present our technique here. We have started our software development process with user’s requirement analysis. We wanted to complete this cycle by taking Beetles back among the farmers and find out about their opinion on such tool. The farmers received the tool positively and provided us with valuable insights presented in the paper.
Skin diseases are among the most common health problems worldwide. As skin diseases normally take... more Skin diseases are among the most common health problems worldwide. As skin diseases normally take a bit time to be cured and need continuous medicine it is sometimes hard to carry on the treatment specially for the poor people in developing countries like Bangladesh. In this article we propose a method that uses .different types of computer vision based techniques to detect different types of skin diseases based on different types information's collected from patients. As per the proposed method there will be two version of this system one will be a desktop application for algorithm develop and checking, and the other version will be a mobile phone application that will be the handy version of the proposed system. The system will be detecting 9 different skin diseases commonly occurred among the poor people in Bangladesh.
Sign language detection and recognition (SLDR) using computer vision is a very challenging task. ... more Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users by computer vision. In this respect, an efficient method is proposed consists of some significant steps and they are, skin detection, preprocessing, different machine learning techniques like PCA and LDA, neural network for training and testing purpose of the system. Various hand sign images are used to test the proposed method and results are presented to provide its effectiveness.
Telemedicine is the process of delivering health care and exchanging information related to healt... more Telemedicine is the process of delivering health care and exchanging information related to health care across distance. Telemedicine is all about a procedure or system where patients get help from doctors from a distance. Interaction between the patient and the doctor through different media like, audio, video, video call, image and information exchanging is also a mean of telemedicine. In this paper we are presenting a telemedicine model which we are developing in the context of Bangladesh. We have designed the system by taking feedback from people of every profession of Bangladesh. As our poor people are the main sufferer of health related issues, so we have mostly emphasized on their thoughts and feedback.
—Multispectral imaging is widely used in remote sensing applications from UAVs and ground-based p... more —Multispectral imaging is widely used in remote sensing applications from UAVs and ground-based platforms. Multispectral cameras often use a physically different camera for each wavelength causing misalignment in the images for different imaging bands. This misalignment must be corrected prior to concurrent multi-band image analysis. The traditional approach for multispectral image registration process is to select a target channel and register all other image channels to the target. There is no objective evidence-based method to select a target. The possibility of registration to some intermediate channel to the target is not usually considered, but could be beneficial if there is no target channel for which direct registration performs well for every other channel. In this paper, we propose an automatic data-driven multispectral image registration framework that determines a target channel, and possible intermediate registration steps based on the assumptions that 1) some reasonable minimum number of control points correspondences between two channels is needed to ensure a low-error registration; and 2) a greater number of such correspondences generally results in lower registration error. Our prototype is tested on three multispectral datasets captured with UAV-mounted multispectral cameras. The resulting registration schemes had more control point correspondences on average than the traditional register-all-to-one-target-channel approach in all of our experiments. For most channels in our three datasets, our registration schemes produced lower back-projection error than the direct-to-target-channel based registration approach.
Skin diseases are among the most common health
problems worldwide. In this article we proposed a ... more Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.
ICCIT-Workshop on Human And Technology (ICCIT-WHAT 2013), Mar 10, 2014
We have presented our work Beetle designed to support farmers in rural area to detect crop diseas... more We have presented our work Beetle designed to support farmers in rural area to detect crop disease. The
system shows promises in terms of disease detection. We present our technique here. We have started our software development process with user’s requirement analysis. We wanted to complete this cycle by taking Beetles back among the farmers and find out about their opinion on such tool. The farmers received the tool positively and provided us with valuable insights presented in the paper.
Skin diseases are among the most common health problems worldwide. As skin diseases normally take... more Skin diseases are among the most common health problems worldwide. As skin diseases normally take a bit time to be cured and need continuous medicine it is sometimes hard to carry on the treatment specially for the poor people in developing countries like Bangladesh. In this article we propose a method that uses .different types of computer vision based techniques to detect different types of skin diseases based on different types information's collected from patients. As per the proposed method there will be two version of this system one will be a desktop application for algorithm develop and checking, and the other version will be a mobile phone application that will be the handy version of the proposed system. The system will be detecting 9 different skin diseases commonly occurred among the poor people in Bangladesh.
Sign language detection and recognition (SLDR) using computer vision is a very challenging task. ... more Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users by computer vision. In this respect, an efficient method is proposed consists of some significant steps and they are, skin detection, preprocessing, different machine learning techniques like PCA and LDA, neural network for training and testing purpose of the system. Various hand sign images are used to test the proposed method and results are presented to provide its effectiveness.
Telemedicine is the process of delivering health care and exchanging information related to healt... more Telemedicine is the process of delivering health care and exchanging information related to health care across distance. Telemedicine is all about a procedure or system where patients get help from doctors from a distance. Interaction between the patient and the doctor through different media like, audio, video, video call, image and information exchanging is also a mean of telemedicine. In this paper we are presenting a telemedicine model which we are developing in the context of Bangladesh. We have designed the system by taking feedback from people of every profession of Bangladesh. As our poor people are the main sufferer of health related issues, so we have mostly emphasized on their thoughts and feedback.
Uploads
Papers by Rahat Yasir
problems worldwide. In this article we proposed a method that
uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed
forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the
colour skin images to extract significant features and later
identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.
system shows promises in terms of disease detection. We present our technique here. We have started our software development process with user’s requirement analysis. We wanted to complete this cycle by taking Beetles back among the farmers and find out about their opinion on such tool. The farmers received the tool positively and provided us with valuable insights presented in the paper.
diseases commonly occurred among the poor people in Bangladesh.
audio, video, video call, image and information exchanging is also a mean of telemedicine. In this paper we are presenting a telemedicine model which we are developing in the context of Bangladesh. We have designed the system by taking feedback from people of every profession of Bangladesh. As our poor
people are the main sufferer of health related issues, so we have mostly emphasized on their thoughts and feedback.
problems worldwide. In this article we proposed a method that
uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed
forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the
colour skin images to extract significant features and later
identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.
system shows promises in terms of disease detection. We present our technique here. We have started our software development process with user’s requirement analysis. We wanted to complete this cycle by taking Beetles back among the farmers and find out about their opinion on such tool. The farmers received the tool positively and provided us with valuable insights presented in the paper.
diseases commonly occurred among the poor people in Bangladesh.
audio, video, video call, image and information exchanging is also a mean of telemedicine. In this paper we are presenting a telemedicine model which we are developing in the context of Bangladesh. We have designed the system by taking feedback from people of every profession of Bangladesh. As our poor
people are the main sufferer of health related issues, so we have mostly emphasized on their thoughts and feedback.