Bilinear Supervised Hashing Based on 2D Image Features
نویسندگان
چکیده
منابع مشابه
Scalable histopathological image analysis via supervised hashing with multiple features
Histopathology is crucial to diagnosis of cancer, yet its interpretation is tedious and challenging. To facilitate this procedure, content-based image retrieval methods have been developed as case-based reasoning tools. Especially, with the rapid growth of digital histopathology, hashing-based retrieval approaches are gaining popularity due to their exceptional efficiency and scalability. Never...
متن کاملImage authentication using LBP-based perceptual image hashing
Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...
متن کاملKernel-Based Supervised Discrete Hashing for Image Retrieval
Recently hashing has become an important tool to tackle the problem of large-scale nearest neighbor searching in computer vision. However, learning discrete hashing codes is a very challenging task due to the NP hard optimization problem. In this paper, we propose a novel yet simple kernel-based supervised discrete hashing method via an asymmetric relaxation strategy. Specifically, we present a...
متن کاملJoint Kernel-Based Supervised Hashing for Scalable Histopathological Image Analysis
Histopathology is crucial to diagnosis of cancer, yet its interpretation is tedious and challenging. To facilitate this procedure, content-based image retrieval methods have been developed as case-based reasoning tools. Recently, with the rapid growth of histopathological images, hashing-based retrieval approaches are gaining popularity due to their exceptional scalability. In this paper, we ex...
متن کاملSupervised Hashing based on Energy Minimization
Recently, supervised hashing methods have attracted much attention since they can optimize retrieval speed and storage cost while preserving semantic information. Because hashing codes learning is NP-hard, many methods resort to some form of relaxation technique. But the performance of these methods can easily deteriorate due to the relaxation. Luckily, many supervised hashing formulations can ...
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 Transactions on Circuits and Systems for Video Technology
سال: 2019
ISSN: 1051-8215,1558-2205
DOI: 10.1109/tcsvt.2019.2891246