Image authentication techniques used to protect the recipients against malicious forgery. In this paper, we propose a new image authentication technique based on digital signature. The authentication is verified by co...Image authentication techniques used to protect the recipients against malicious forgery. In this paper, we propose a new image authentication technique based on digital signature. The authentication is verified by comparing the features of the each block in tested image with the corresponding features of the block recorded in the digital signature. The proposed authentication scheme is capable of distinguishing visible but non-malicious changes due to common processing operations from malicious changes. At last our experimental results show that the proposed scheme is not only efficient to protect integrity of image, but also with low computation, which are feasible for practical applications.展开更多
We present a novel watermarking approach based on classification for authentication, in which a watermark is embedded into the host image. When the marked image is modified, the extracted watermark is also different t...We present a novel watermarking approach based on classification for authentication, in which a watermark is embedded into the host image. When the marked image is modified, the extracted watermark is also different to the original watermark, and different kinds of modification lead to different extracted watermarks. In this paper, different kinds of modification are considered as classes, and we used classification algorithm to recognize the modifications with high probability. Simulation results show that the proposed method is potential and effective.展开更多
Image forensics is a form of image analysis for finding out the condition of an image in the complete absence of any digital watermark or signature.It can be used to authenticate digital images and identify their sour...Image forensics is a form of image analysis for finding out the condition of an image in the complete absence of any digital watermark or signature.It can be used to authenticate digital images and identify their sources.While the technology of exemplar-based inpainting provides an approach to remove objects from an image and play visual tricks.In this paper, as a first attempt, a method based on zero-connectivity feature and fuzzy membership is proposed to discriminate natural images from inpainted images.Firstly, zero-connectivity labeling is applied on block pairs to yield matching degree feature of all blocks in the region of suspicious, then the fuzzy memberships are computed and the tampered regions are identified by a cut set.Experimental results demonstrate the effectiveness of our method in detecting inpainted images.展开更多
The identification of sugarcane varieties through remote sensing is studied to reduce the time taken to identify in the field, also is useful to identify non-certified varieties and to monitor the adoption of new vari...The identification of sugarcane varieties through remote sensing is studied to reduce the time taken to identify in the field, also is useful to identify non-certified varieties and to monitor the adoption of new varieties. The purpose of this study is to evaluate the Landsat 7 ETM＋ images to discriminate varieties CC85-92 and CC84-75 in the Cauca river valley in Colombia. The method used to measure the spectral separability between varieties was Jeffries-Matusita. The results indicated that the only period where a clear discrimination of the varieties is between 4th and 5th months, with a global precision of 80.8% and kappa index 0.62. The proposed methodology and preliminary results show that remote sensing is a useful tool for monitoring and identification of varieties and could be used for identification of varieties already registered and planted in other countries without the consent of their true creators.展开更多
In the context of new risks and threats associated to nuclear, biological and chemical （NBC） attacks, and given the shortcomings of certain analytical methods such as principal component analysis （PCA）, a neural n...In the context of new risks and threats associated to nuclear, biological and chemical （NBC） attacks, and given the shortcomings of certain analytical methods such as principal component analysis （PCA）, a neural network approach seems to be more accurate. PCA consists in projecting the spectrum of a gas collected from a remote sensing system in, firstly, a three-dimensional space, then in a two-dimensional one using a model of Multi-Layer Perceptron based neural network. It adopts during the learning process, the back propagation algorithm of the gradient, in which the mean square error output is continuously calculated and compared to the input until it reaches a minimal threshold value. This aims to correct the synaptic weights of the network. So, the Artificial Neural Network （ANN） tends to be more efficient in the classification process. This paper emphasizes the contribution of the ANN method in the spectral data processing, classification and identification and in addition, its fast convergence during the back propagation of the gradient.展开更多
文摘Image authentication techniques used to protect the recipients against malicious forgery. In this paper, we propose a new image authentication technique based on digital signature. The authentication is verified by comparing the features of the each block in tested image with the corresponding features of the block recorded in the digital signature. The proposed authentication scheme is capable of distinguishing visible but non-malicious changes due to common processing operations from malicious changes. At last our experimental results show that the proposed scheme is not only efficient to protect integrity of image, but also with low computation, which are feasible for practical applications.
文摘We present a novel watermarking approach based on classification for authentication, in which a watermark is embedded into the host image. When the marked image is modified, the extracted watermark is also different to the original watermark, and different kinds of modification lead to different extracted watermarks. In this paper, different kinds of modification are considered as classes, and we used classification algorithm to recognize the modifications with high probability. Simulation results show that the proposed method is potential and effective.
文摘Image forensics is a form of image analysis for finding out the condition of an image in the complete absence of any digital watermark or signature.It can be used to authenticate digital images and identify their sources.While the technology of exemplar-based inpainting provides an approach to remove objects from an image and play visual tricks.In this paper, as a first attempt, a method based on zero-connectivity feature and fuzzy membership is proposed to discriminate natural images from inpainted images.Firstly, zero-connectivity labeling is applied on block pairs to yield matching degree feature of all blocks in the region of suspicious, then the fuzzy memberships are computed and the tampered regions are identified by a cut set.Experimental results demonstrate the effectiveness of our method in detecting inpainted images.
文摘The identification of sugarcane varieties through remote sensing is studied to reduce the time taken to identify in the field, also is useful to identify non-certified varieties and to monitor the adoption of new varieties. The purpose of this study is to evaluate the Landsat 7 ETM＋ images to discriminate varieties CC85-92 and CC84-75 in the Cauca river valley in Colombia. The method used to measure the spectral separability between varieties was Jeffries-Matusita. The results indicated that the only period where a clear discrimination of the varieties is between 4th and 5th months, with a global precision of 80.8% and kappa index 0.62. The proposed methodology and preliminary results show that remote sensing is a useful tool for monitoring and identification of varieties and could be used for identification of varieties already registered and planted in other countries without the consent of their true creators.
文摘In the context of new risks and threats associated to nuclear, biological and chemical （NBC） attacks, and given the shortcomings of certain analytical methods such as principal component analysis （PCA）, a neural network approach seems to be more accurate. PCA consists in projecting the spectrum of a gas collected from a remote sensing system in, firstly, a three-dimensional space, then in a two-dimensional one using a model of Multi-Layer Perceptron based neural network. It adopts during the learning process, the back propagation algorithm of the gradient, in which the mean square error output is continuously calculated and compared to the input until it reaches a minimal threshold value. This aims to correct the synaptic weights of the network. So, the Artificial Neural Network （ANN） tends to be more efficient in the classification process. This paper emphasizes the contribution of the ANN method in the spectral data processing, classification and identification and in addition, its fast convergence during the back propagation of the gradient.
