Cross-Domain Co-Occurring Feature for Visible-Infrared Image Matching
نویسندگان
چکیده
منابع مشابه
Deep sketch feature for cross-domain image retrieval
Deep learning has been proven be very effective for various image recognition tasks, e.g., image classification, semantic segmentation, image retrieval, shape classification etc. However, existing works on deep learning for image recognition mainly focus on either natural image data or binary shape data. In this paper, we show that deep convolutional neural networks (DCNN) is also suitable for ...
متن کاملAn extended feature set for blind image steganalysis in contourlet domain
The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We us...
متن کاملFeature Point Descriptors: Infrared and Visible Spectra
This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set...
متن کاملVisible and Infrared Sensors Fusion by Matching Feature Points of Foreground Blobs
Foreground blobs in a mixed stereo pair of videos (visible and infrared sensors) allow a coarse evaluation of the distances between each blob and the uncalibrated cameras. The main goals of this work are to find common feature points in each type of image and to create pairs of corresponding points in order to obtain coarse positionning of blobs in space. Feature points are found by two methods...
متن کاملSample-oriented Domain Adaptation for Image Classification
Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. The conventional image processing algorithms cannot perform well in scenarios where the training images (source domain) that are used to learn the model have a different distribution with test images (target domain). Also, many real world applicat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2820680