Fusion of near-infrared and RGB images on a FPGA using high level synthesis tool

Several applications utilizing a set of red green blue (RGB) and near infrared (NIR) images have been emerging over recent years. The present work proposes a technique of enhancing an image by combining color (RGB) and near infrared information (NIR). In order to fuse the two types of images, the NIR-channel is considered as a luminance counterpart to the visible image. International standard database (RGB-NIR Scene Dataset) is used in this work for image fusion. The objective of the paper is to present a simple and hardware efficient fusion method, where the original RGB image is converted into two different color spaces, namely, HSV and YCbCr. Later, the luminance channel of the RGB image is replaced with the near infrared channel, thereby obtaining a fused enhanced image. The above procedure is effectively implemented on FPGA using the Xilinx HLS tool. RGB-NIR dataset is used in the present work for testing the proposed image fusion algorithm, and the quality of the fused image is measured through peak signal to noise ratio (PSNR). The experimental results indicate that HSV color space is more efficient in image fusion compared to YCbCr color space based on the average PSNR values of approximately 29db for HSV and 25db for YCbCr for various images, respectively. Finally, this complete fusion algorithm is implemented on Xilinx Nexys4 FPGA board to be able to obtain real-time outputs in the form of vivid, contrasted images that are pleasing to the observers. The experimental results illustrate that the Xilinx FPGA utilizes only 50% of the available hardware resources and consumes approximately 5.3 Watts to implement the fusion process.

An Improved Gesture Segmentation Method for Gesture Recognition Based on CNN and YCbCr

With the continuous improvement of people’s requirements for interactive experience, gesture recognition is widely used as a basic human-computer interaction. However, due to the environment, light source, cover, and other factors, the diversity and complexity of gestures have a great impact on gesture recognition. In order to enhance the features of gesture recognition, firstly, the hand skin color is filtered through YCbCr color space to separate the gesture region to be recognized, and the Gaussian filter is used to process the noise of gesture edge; secondly, the morphological gray open operation is used to process the gesture data, the watershed algorithm based on marker is used to segment the gesture contour, and the eight-connected filling algorithm is used to enhance the gesture features; finally, the convolution neural network is used to recognize the gesture data set with fast convergence speed. The experimental results show that the proposed method can recognize all kinds of gestures quickly and accurately with an average recognition success rate of 96.46% and does not significantly increase the recognition time.

Deteksi Api pada Video dengan Gaussian Mixture Model Untuk Deteksi Gerakan Dan Segmentasi Warna Api Dalam Ruang Warna YCbCr

Fire is a disaster that can endanger lives and cause property loss. The solution to detect fire that is commonly used today is to use a sensor. Fire sensors can be used together with surveillance cameras (CCTV) which are now being installed in many office buildings. This study tries to build a model for detecting fire in video with a digital image processing approach using the Gaussian Mixture Model for motion detection and fire color segmentation in the YCbCr color space. The model is then tested with metrics for accuracy, precision, recall, and processing speed. The dataset used is in the form of videos with small, medium, large fire sizes, and videos that only have fire-like objects. The test results show that the algorithm is able to detect fire when the size of the fire is not too small or the position of the fire is close enough to the camera. For videos with a resolution of 800x600 and a framerate of 30 fps, it can achieve 66.89% accuracy, 73.77% precision, and 66.66% recall. The performance during the day is relatively better than at night. Algorithm processing speed is too slow to be implemented in real-time

Robust Digital Image Watermarking in YCbCr Color Space using Hybrid Method: A Survey

This paper provides the conceptual framework on image watermarking which is widely used for security purpose within the epoch of data and Communication Technology. Image watermarking is predicated on the concept that the signal may carry several different watermarks at the identical time. The signal is also audio, pictures or video. Security issue in watermarking is because of enlargement of internet within the present paper the primary phase detailed description of watermarking has been on condition that data set are prepared on which watermarking technique are executed. In the second phase detailed working of the various techniques of image watermarking have to locate a selected watermarking technique which is able to provide appropriate ends up in term of PSNR and interval and various attacks are tested on images so implemented method must stand against various attacks. In final phase reverse process are executed to extract host and watermark image. There are many viable attacks. Spotting is an algorithm which is applied to the attacked signal to infusion the watermark from it. During the research work our main focus will be to enhance various critical paramters like PSNR and execution time so that better outcome can be attained.

Robust Digital Image Watermarking in YCbCr Color Space using Hybrid Method

The image watermarking is widely used to provide the security. This paper provides the conceptual framework on image watermarking which is widely used for security purpose within the epoch of data and communication technology. Detailed discuss has been provided on the basis of the three phases. In the first phase of present paper focus has been made on image watermarking and data set will be prepared on which watermarking technique will be executed. Second phase need to locate a specific watermarking technique [LWT- WALSH HADMARD-SVD] which will provide appropriate results in term of PSNR and processing time. In second phase various attacks will be tested on images so that implemented method must stand against various attacks. Last phase emphasise on reverse process will be executed to extract cover and watermark image. Proposed technique is based on the secure encryption watermark .It is associated with image encryption. The encryption algorithm had been introduced in which watermarking information was based on the size of an image. It is clear from the outcomes of the hybrid proposed technique shows that it provides more security than the existing technique. Proposed techniques provide high level of security as compared to existed technology.

Classification of Anemia with Digital Images of Nails and Palms using the Naive Bayes Method

Purpose: Early detection of anemia based on nails and palms images by applying the Naive Bayes method, as well as to measure the level of accuracy in detecting anemia.Design/methodology/approach: Using the Naive Bayes method. System development uses the waterfall method.Findings/result: Based on the results of the tests that have been carried out, the resulting accuracy is 87.5% with varying light intensities and is 92.3% by using a light intensity of 5362 Lux.Originality/value/state of the art: The difference between this study and previous research is in the image pre-processing method and classification method. In this study, the images of the nails and palms were converted to the YCbCr color space to be segmented and color features extracted. Then the color features will be classified using the Naive Bayes classification method. The output of this system is the result of the input image classification, whether normal or anemic.