In this paper, a novel human activity recognition method is presented. The proposed solution uses a single stationary camera in order to detect common human activities like: hand waving, walking, running etc. Unlike o...
详细信息
In this paper, a novel human activity recognition method is presented. The proposed solution uses a single stationary camera in order to detect common human activities like: hand waving, walking, running etc. Unlike other methods which use different kinds of characteristic point descriptors in order to describe human poses, the proposed solution uses a CDVS descriptor which is part of the MPEG-7 standard. This allows the efficient calculation of a compact descriptor in a camera. The main goal of this work is to propose an efficient application of CDVS to describe and recognize different human activities. The experiments were performed on the Weizmann and KTH datasets. The obtained results prove the high accuracy of human activity recognition system with CDVS.
The detection of double JPEG compression with the same quantization matrix is a challenging problem in image forensics. In this paper, a CNN framework is proposed to solve this problem. This framework contains a prepr...
详细信息
ISBN:
(纸本)9781728102436;9789881476852
The detection of double JPEG compression with the same quantization matrix is a challenging problem in image forensics. In this paper, a CNN framework is proposed to solve this problem. This framework contains a preprocessing layer and a well-designed CNN. In the preprocessing layer, the rounding and truncation error images are extracted from continuous recompressed input samples and then fed into the following CNN. In the design of the CNN architecture, several advanced techniques are carefully considered to prevent overfitting, such as 1×1 convolutional kernel and global average pooling layer. The performance of proposed framework is evaluated on the public available image dataset (BOSSbase) with various quality factors (QF). Experimental results have shown the proposed CNN framework performs better than the state-of-the-art method based on hand-crafted features.
The paper presents an efficient algorithm for post compression optimal rate allocation and packetization within JPEG2000 encoding. JPEG2000, the new ISO/ITU-T standard for still image coding, has been shown to provide...
详细信息
The paper presents an efficient algorithm for post compression optimal rate allocation and packetization within JPEG2000 encoding. JPEG2000, the new ISO/ITU-T standard for still image coding, has been shown to provide superior coding efficiency to the previous standard, JPEG. However, the added efficiency of JPEG2000 comes at the cost of increased computational requirements. To improve the computational efficiency of JPEG2000, we propose a new algorithm for JPEG2000 rate allocation and packetization utilizing the D-heap data structure. Implemented in Jasper and tested on five reference images, this algorithm provides a speedup for JPEG2000's rate allocation and packetization of 15.9 times on average, and enables an average overall speedup of 33% for JPEG2000 encoding.
A recently introduced algebraic integer encoding scheme allows low complexity, virtually error free computation of the DCT and IDCT. Efficiencies can be introduced into this method, but at the expense of some increase...
详细信息
ISBN:
(纸本)0780366859
A recently introduced algebraic integer encoding scheme allows low complexity, virtually error free computation of the DCT and IDCT. Efficiencies can be introduced into this method, but at the expense of some increase in error. In this paper, a modification to the encoding scheme is introduced for specific architectures which provides increased implementation efficiency, but with no sacrifice in accuracy. We provide a theoretical study of this new approach and illustrate the technique using selected DCT and IDCT algorithms.
Image classification models have demonstrated remarkable performance across various applications, yet they remain vulnerable to adversarial attacks, which can significantly impair their accuracy and reliability. This ...
详细信息
ISBN:
(数字)9798331533137
ISBN:
(纸本)9798331533144
Image classification models have demonstrated remarkable performance across various applications, yet they remain vulnerable to adversarial attacks, which can significantly impair their accuracy and reliability. This paper presents a new hybrid defense scheme to increase adversarial robustness in image classifiers. The approach combines two complementary techniques: adversarial training and input transformations. Adversarial training is implemented using the Projected Gradient Descent (PGD) attack to generate robust features by exposing the model to adversarial samples during training. Concurrently, input transformations, including random resizing, JPEG compression, and noise injection, disrupt adversarial perturbations and preserve critical image features. The integration of these methods results in a multi-layered defense mechanism that improves the model's resilience to a range of adversarial attacks. Extensive experiments are conducted on standard image classification datasets, evaluate the efficacy of the proposed scheme against various attack methods, including FGSM and PGD. The results demonstrate that the hybrid defense strategy significantly enhances robustness while maintaining competitive performance on clean images. This research offers a comprehensive solution for improving the reliability of image classifiers in adversarial settings and provides insights into balancing robustness and accuracy.
We present the ***-VBR winning candidate codec recently selected by Question 9 of Study Group 16 (Q9/16) of ITU-T as a baseline for the development of a scalable solution for wideband speech and audio compression at r...
详细信息
We present the ***-VBR winning candidate codec recently selected by Question 9 of Study Group 16 (Q9/16) of ITU-T as a baseline for the development of a scalable solution for wideband speech and audio compression at rates between 8 kb/s and 32 kb/s. The Q9/16 codec is an embedded codec comprising 5 layers where higher layer bitstreams can be discarded without affecting the decoding of the lower layers. The two lower layers are based on the CELP technology where the core layer takes advantage of signal classification based encoding. The higher layers encode the weighted error signal from lower layers using overlap-add transform coding. The codec has been designed with the primary objective of a high-performance wideband speech coding for error- prone telecommunications channels, without compromising the quality for narrowband/wideband speech or wideband music signals. The codec performance is demonstrated with selected test results.
In this paper we describe a structural compression technique to be used for document text image storage and retrieval. The primary objective is to provide an efficient representation, storage, transmission and display...
详细信息
In this paper we describe a structural compression technique to be used for document text image storage and retrieval. The primary objective is to provide an efficient representation, storage, transmission and display. A secondary objective is to provide an encoding which allows access to specified regions within the image and facilitates traditional document processing operations without requiring complete decoding. We describe an algorithm which symbolically decomposes a document image and structurally orders the error bitmap based on a probabilistic model. The resultant symbol and error representations lend themselves to reasonably high compression ratios and are structured so as to allow operations directly on the compressed image. The compression scheme is implemented and compared to traditional compression methods.
The objective of this research is to design a new JPEG-based compression scheme which simultaneously considers the security issue. Our method starts from dividing image into non-overlapping blocks with size 8×8. ...
详细信息
The objective of this research is to design a new JPEG-based compression scheme which simultaneously considers the security issue. Our method starts from dividing image into non-overlapping blocks with size 8×8. Among these blocks, some are used as reference blocks and the rest are used as query blocks. A query block is the combination of the residual and the resultant of a filtered reference block. We put our emphasis on how to estimate an appropriate filter and then use it as part of a secret key. With both reference blocks and the residuals of query blocks, one is able to encode secured images using a correct secret key. The experiment results will demonstrate that how different secret keys can control the quality of restored image based on the priority of authority.
Recovering deleted files play an important role in a digital forensic investigation. When a file is deleted, only pointers that link file's metadata to its content are deleted and metadata entry is marked as delet...
详细信息
Recovering deleted files play an important role in a digital forensic investigation. When a file is deleted, only pointers that link file's metadata to its content are deleted and metadata entry is marked as deleted. As long as data is not overwritten or wiped, deleted data will remain in unallocated space. One of the methods that can be used to recover these deleted files is file carving. File carving reconstructs files only based on their content unlike traditional data recovery methods that use metadata that points to the content. It is mainly done using headers and footers of file types. One of the primary challenges in file carving is to recover deleted files that were fragmented. When a file is fragmented, carving only based on header and footer will produce corrupted file. So this paper discusses a method for carving fragmented document and image files from a FAT32 formatted USB drive.
暂无评论