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In this project, a lung nodule detection method based on deep learning is proposed for thoracic MR images. The non-text MSERs are removed by employing appropriate filters. Face Recognition using Image Processing for Visually Challenged In this paper the face recognition is done for the visually challenged people. The first convolutional layer of the CNN serves as the preprocessing module to efficiently obtain the tampering artifacts. With the help of OpenCV, The research has been implemented. An extension of a benchmark dataset Food-101 is also created to include sub-continental foods. A stored database of the subjects is manipulated using image processing techniques to accomplish this task. Finally, an efficient CNN with asymmetric kernels is used to be the classifier of traffic signs. The generated image representation is then condensed by a simple feature fusion technique, i.e., regional pooling, to obtain the final discriminative feature. But it may not be so simple for a computer. We compare the result of our model accuracy and computational time with CNN-recurrent neural network (RNN) combined model. The method elaborated utilizes a segmentation algorithm which can successfully extract the iris under varying lighting conditions with the help of machine learning. There are two major techniques available to detect hand motion or gesture such as vision and non-vision technique and convert the detected information into voice through raspberry pi. Additionally, we make a simple analysis on how those methods reduce the parameters and the cost of computation in training process. The paper describes a deep network based system specialized for ball detection in long shot videos. In this paper, we propose an acceleration of the seam carving method by expanding the width of the seam making it multiple-pixel wide seam carving. The final segmented retina vessels contain more noise with low classification accuracy. In this project a novel methodology to perform iris segmentation and gaze recognition has been introduced and described. Reference Paper (IEEE 2019)Heart Rate Variability-Based Driver Drowsiness Detection and Its Validation With EEGPublished in: IEEE Transactions on Biomedical Engineering ( Volume: 66 , Issue: 6 , June 2019 )https://ieeexplore.ieee.org/document/8520803, Automated recognition of human activities or actions has great significance as it incorporates wide-ranging applications, including surveillance, robotics, and personal health monitoring.This paper presents a viable multimodal feature-level fusion approach for robust human action recognition, which utilizes data from multiple sensors, including RGB camera, Reference Paper IEEE 2019Robust Human Activity Recognition Using Multimodal Feature-Level FusionPublished in: IEEE Access ( Volume: 7 )https://ieeexplore.ieee.org/document/8701429. We proposed four new feasible network schemes, and the best network model fully dilated convolution combining U-Net (FD-UNet) is obtained by training and testing on the same datasets. In the second phase, an interpolation of nonuniformly spaced samples based on pixel gray correction is proposed to get the high resolution (HR) image. An automizing process for bacteria recognition becomes attractive to reduce the analyzing time and increase the accuracy of diagnostic process. As a first step, we used only four gestures. In the proposed multi-scale information fusion module (MSIF), parallel convolution layers with different dilation rates are used, so that the model can obtain more dense feature information and better capture retinal vessel information of different sizes. The word steganography combines the Greek words steganos , meaning covered, concealed, or protected, and graphein meaning writing. Further, artificial neural network (ANN) is shown to provide better performance than Naive Bayes and K-Nearest Neighbours models. The acquired results show that our proposed inpainting method gives an outstanding performance to fill the corrupted areas and to remove objects. Navigation. However, above all, crop disease is the crucial factor and causes 20-30% reduction of the productivity in case of its infection. The proposed system consists of a camera which detects the commodity using Deep Learning techniques and a load cell which measures the weight of the commodity attached to the shopping cart. Three different hardware-architecture variants, two for image watermarking and one for video (pipelined), are proposed, which reutilize the already small arithmetic units in different computation steps, to further reduce implementation cost. Reference Paper IEEE 2019Adaptive Multiple-pixel Wide Seam CarvingPublished in: 2019 National Conference on Communications (NCC)https://ieeexplore.ieee.org/document/8732245. Reference Paper IEEE 2019Hiding Images Within ImagesPublished in: IEEE Transactions on Pattern Analysis and Machine Intelligence ( Early Access )https://ieeexplore.ieee.org/document/8654686. According to gesture Recognized, various tasks can be performed like turning on the fan or lights. Gait is a cutting-edge biometric for recognizing people. In the end, the CTDRNet is implemented and evaluated with an accuracy of 96% and processing rate of 2.5 fps. Latest version. shopping malls have become an integral part of life and people in cities often go to shopping malls in order to purchase their daily requirements. This project proposes a Convolutional Neural Network (CNN), for classification problem and Faster Region based Convolutional Neural Network (Faster R-CNN) for segmentation problem with reduced number of computations with a higher accuracy level. Reference Paper IEEE 2019Visually Lossless Compression of Dental ImagesPublished in: 2019 IEEE 39th International Conference on Electronics and Nanotechnology (ELNANO)https://ieeexplore.ieee.org/document/8783218. This way, for every periocular region, the CNN receives multiple samples of different ocular classes, forcing it to conclude that such regions should not be considered in its response. All it takes is snapping a screenshot of a photo or video, and the app will show you relevant products in online stores, as well as similar items from their vast and constantly-updated catalog. There are two kinds of methods that are currently popular in developed face recognition pattern namely, Eigenface method and Fisherface method. The user can interact solely through his/her voice with Olivia (the virtual assistant) to get any his/her work done around the house. Reference Paper IEEE 2019 Fused Convolutional Neural Network for White Blood Cell Image Classification Published in: 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) https://ieeexplore.ieee.org/document/8669049. Reference Paper IEEE 2019Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural NetworksPublished in: IEEE Access ( Volume: 7 )https://ieeexplore.ieee.org/document/8706936, Reference Paper IEEE 2018An image preprocessing method for kidney stone segmentation in CT scan imagesPublished in: 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM), Tuberculosis(TB) in India is the worlds largest TB epidemic [1] leading to 480,000 deaths every year [2]. Mobile application has been identified as the best platform for the expert system tool to reach as many users as possible. The second stage, leverages Deep learning architecture. Reference Paper IEEE 2019Brain tumor Classification and Segmentation using Faster R-CNNPublished in: 2019 Advances in Science and Engineering Technology International Conferences (ASET)https://ieeexplore.ieee.org/document/8714263. It may be very easy for humans like you and me to recognise different images, such as images of animals. Reference Paper IEEE 2019Gait Recognition for Saudi Costume Using Kinect Skeletal TrackingPublished in: 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS)https://ieeexplore.ieee.org/document/8769552. These transformation range from simple image manipulations to sophisticated machine learning-based adversaries. If the conditions is true, unlock the vehicle. Reference Paper IEEE 2019Deep-PRWIS: Periocular Recognition Without the Iris and Sclera Using Deep Learning FrameworksPublished in: IEEE Transactions on Information Forensics and Security ( Volume: 13 , Issue: 4 , April 2018 )https://ieeexplore.ieee.org/document/8101565. According to the performance of AlexNet in classification, it was used to diagnose benign and malignant lesions. The noise chart of this image is equipped with a multi-resolution failure filter and gives the output to the classifiers. Flow can identify millions of products like DVDs and CDs, book covers, video games, and packaged household goods for example, the box of your favorite cereal. A real-time intelligent video analytics offers advanced monitoring capabilities that gives sophisticated video surveillance to recognize the abnormal activities. Reference Paper IEEE 2019 Smart Home With Virtual Assistant Using Raspberry Pi Published in: 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence) https://ieeexplore.ieee.org/document/8776918. Building projects can be very challenging on image processing, For a smart service auto, ANPR is helping promoting development, personalizing classic application and increasing productivity for clients and workers. Face detection is the pre-step for face recognition that is performed using Haar-like features. Our emotion is revealed by the exp ressions in our face. The Top 69 Image Recognition Open Source Projects. We present a deep learning system for automatic logo detection in real world images. A machine learning algorithm ESRT (enhanced streaming random tree) model is proposed. Matlab Code for LSB Steganography Steganography is a branch of information hiding which allows the people to communicate secretly. PACS). For this reason, in this paper, we introduce computation optimizations of the implemented algorithm to keep the integer part of arithmetic operations at optimal size, and, hence, arithmetic units as small as possible. The system is smart enough to identify and differentiate between the owner and stranger using face recognition and act accordingly. Tool : This project is based on Machine learning, We can provide a lot of data set as an Input to the software tool which will be recognized by the machine and similar pattern will be taken out from them. Iris, fingerprint, and three-dimensional face recognition technologies used in mobile devices face obstacles owing to price and size restrictions by additional cameras, lighting, and sensors. First, we divide each video sequence into multiple video clips and sample the frames of each video clip. In this context, an effective approach is suggested for automated text detection and recognition for the natural scenes. These findings are based on Computer Vision Challenge on Bengali HandWritten Digit Recognition (2018) competition submissions. Categories > Machine Learning > Image Recognition. There has been a rapid increase in dietary ailments during the last few decades, caused by unhealthy food routine. Your email address will not be published. For these applications, an accurate and reliable image-based detection system is critically important. Computer Vision Project Idea Contours are outlines or the boundaries of the shape. It has an accuracy of 98.5% using 2500 variant images in a class. The text recognition is performed by employing an Optical Character Recognition (OCR) function. A deep residual network is used to address the degradation of recognition performance caused by misalignment and illumination variation occurring during image acquisition. This is known as the eye fix or point of fixation. These samples are used for data augmentation purposes and feed the learning phase of the CNN, always considering as label the ID of the periocular part. The Image can be of handwritten document or Printed document. Image inpainting is a process of completion of missing places by using other undamaged sections of the image or removal of unwanted objects of the image. Reference Paper IEEE 2019Deep CNN for removal of salt and pepper noisePublished in: IET Image Processing ( Volume: 13 , Issue: 9 , 7 18 2019 )https://ieeexplore.ieee.org/document/8768516. The realtime semantic segmenter S is used to refine the foreground segmentation outputs as feedbacks for improving the model updating accuracy. The image analysis and detection has been very significant in various applications. Thereby, the amount of actual defects that are falsely classified as negative are minimized. However, to end up with such implementations, proper selection of watermarking techniques is not enough. Reference Paper IEEE 2019Review on Multi-Model Medical Image FusionPublished in: 2019 International Conference on Communication and Signal Processing (ICCSP)https://ieeexplore.ieee.org/document/8697906. During the test phase, samples are provided without any segmentation mask and the network naturally disregards the ocular components, which contributes for improvements in performance. Reference Paper IEEE 2019 Image Deblocking Detection Based on a Convolutional Neural Network Published in: IEEE Access ( Volume: 7 ) https://ieeexplore.ieee.org/document/8649625. Because uncertainty and impreciseness among the symptoms in diagnosis process, we choose fuzzy logic based design. Reference Paper IEEE 2019 Pedestrian Detection Based on YOLO Network Model Published in: 2018 IEEE International Conference on Mechatronics and Automation (ICMA) https://ieeexplore.ieee.org/document/8484698. Therefore, in this paper, we propose a DCNN structure named as D-Net. In this paper, we have explored the use of Kinect for gait identification of Saudi persons who are wearing thobe or abaya. Our method employs different deep learning models for accurate food identification. Reference Paper IEEE 2019Fingerprint Recognition System using MATLABPublished in: 2019 International Conference on Automation, Computational and Technology Management (ICACTM)https://ieeexplore.ieee.org/document/8776680. In this system, Olivia can interact with the stranger at the door in case the owner is not present at home and will notify the owner about the visit using Email and SMS along with the image of the stranger. This is significant to ensure the ability of the proposed approach to tackle security threats that may face medical images during routine medical practices. This paper presents a simple method of tracking and counting fish images using an image processing technique. The algorithm shows better detection rate and accuracy compared with Bayesian classifiers available in WEKA. A dataset in Attribute Relation File Format is created for shadow and non-shadow images. Because sometimes you just need to know whether the picture in front of you contains a hot-dog. One of them is steganography. In this work vehicles and pedestrians are considered objects of interest. This work assures the achievement of the identified particular requirements of digital watermarking when applied to digital medical images and also provides robust controls within medical imaging pipelines to detect modifications that may be applied to medical images during viewing, storing and transmitting. It also allows scanning business cards to add new people to your contacts swiftly. Reference Paper IEEE 2019Neural Network-Based Vehicle and Pedestrian Detection for Video Analysis SystemPublished in: 2019 8th Mediterranean Conference on Embedded Computing (MECO)https://ieeexplore.ieee.org/document/8760125. The results show that the recognition performance by our method exceeds in those of conventional methods. VGG-16 based CNN is used to extract the feature from the given image. We fuse the feature maps of two convolutional layers by using the operation of max-pooling to give input to the fully connected neural network layer. This paper proposes foreground segmentation algorithm powered by the convolutional neural network. In order to identify the food accurately in the system, we use deep convolutional neural networks to classify 10000 high-resolution food images for system training. The traditional image denoising algorithm is based on filter design or interpolation algorithm. Furthermore, the proposed scheme exhibits very good performance in terms of the mean squared error (MSE) and the peak signal to noise ratios (PSNR). The high sensitivity of our method gives it the potential to evolve into an effective and accessible screening tool for TB detection, when trained at scale, Reference Paper IEEE 2018Automated Tuberculosis detection using Deep LearningPublished in: 2018 IEEE Symposium Series on Computational Intelligence (SSCI)https://ieeexplore.ieee.org/document/8628800. The management of the attendance can be a great burden on the teachers if it is done by hand. The results demonstrate that the novel INAR-SSD model provides a high-performance solution for the early diagnosis of apple leaf diseases that can perform real-time detection of these diseases with higher accuracy and faster detection speed than previous methods. Image processing using the MATLAB can be done using two ways such as Editor Window or GUI. No worries, we will explain everything in detail. Reference Paper IEEE 2019Automated Breast Ultrasound Lesions Detection Using Convolutional Neural NetworksPublished in: IEEE Journal of Biomedical and Health Informatics ( Volume: 22 , Issue: 4 , July 2018 )https://ieeexplore.ieee.org/document/8003418. Reference Paper IEEE 2019 Surface Defect Detection for Automated Inspection Systems using Convolutional Neural Networks Published in: 2019 27th Mediterranean Conference on Control and Automation (MED) https://ieeexplore.ieee.org/document/8798497.

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