12136049
Content-Based Synchronization Using the Local Invariant Feature for Robust Watermarking
This paper addresses the problem of content-based synchronization for robust watermarking. Synchronization is a process of extracting the location to embed and detect the signature, copyright information, so that it is crucial for the robustness of the watermarking system. In this paper, we will review representative content-based approaches and propose a new synchronization method based on the scale invariant feature transform. In content-based synchronization approaches, it is important to extract robust features even with image distortions and we suspect that the consideration of local image characteristics will be helpful. The scale invariant feature transform regards these characteristics and is invariant to noise, spatial filtering, geometric distortions, and illumination changes of the image. Through experiments, we will compare the proposed method with representative content-based approaches and show the appropriateness for robust watermarking.
7718842
Averaging attack resilient video fingerprinting
This paper addresses an effective technique for digital fingerprinting for video. The code modulation technique, that uses an averaging collusion resilient fingerprint code derived from BIBD, is a robust method against averaging attacks. In this paper, we propose a new fingerprint code based on GD-PBIBD theory that is efficient in designing the fingerprint code and describe an effective method to embed and detect the fingerprint code, in which the merits of orthogonal modulation and coded modulation techniques are combined. To analyze the performance, we apply our method to video applications using a spread-spectrum watermarking technique in the spatial domain and the results show the proposed method is effective for fingerprint code embedding and detection.
16122349
Feature-Based Image Watermarking Method Using Scale-Invariant Keypoints
This paper addresses feature-based image watermarking methods for digital contents. Most previous watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. In order to synchronize the watermark location, watermark synchronization should be performed. One solution for watermark synchronization is to use image features. This paper describes a feature-based watermarking method based on scale-invariant keypoints. We extract feature points from the scale-invariant keypoint extractor and then decompose feature points into a set of disjoint triangles. These triangles are watermarked by an additive spread-spectrum method on the spatial domain. We perform an intensive simulation in comparison with other feature-based watermarking methods using 100 test images. Results show that the proposed method is considerably robust against both geometric distortion attacks and signal processing attacks listed in Stirmark 3.1.
5620319
Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry
This paper addresses the problem of generating digital elevation models from satellite images taken by linear pushbroom cameras. Since there exist unique geometric properties for linear pushbroom images, we argue that the conventional DEM generation schemes developed for perspective images are not suitable for satellite images. Using the geometric properties of linear pushbroom images, we design a new matching strategy optimized for linear pushbroom image in three aspects: conjugate search method, correlation patch design and match sequence determination. We will discuss in what aspect conventional approaches and our new approach differ and show how performance has improved by hiring proper techniques. A series of experiments using SPOT panchromatic stereo pairs showed that our approach outperformed conventional approaches in terms of accuracy and processing time. q 2003 Elsevier B.V. All rights reserved.
46208894
Evaluation of Feature Extraction Techniques for Robust Watermarking
This paper addresses feature extraction techniques for robust watermarking. Geometric distortion attacks desynchronize the location of the inserted watermark and hence prevent watermark detection. Watermark synchronization, which is a process of finding the location for watermark insertion and detection, is crucial to design robust watermarking. One solution is to use image features. This paper reviews feature extraction techniques that have been used in featurebased watermarking: the Harris corner detector and the Mexican Hat wavelet scale interaction method. We also evaluate the scale-invariant keypoint extractor in comparison with other techniques in aspect of watermarking. After feature extraction, the set of triangles is generated by Delaunay tessellation. These triangles are the location for watermark insertion and detection. Redetection ratio of triangles is evaluated against geometric distortion attacks as well as signal processing attacks. Experimental results show that the scale-invariant keypoint extractor is appropriate for robust watermarking.
7138459
Comparison of Feature Extraction Techniques for Watermark Synchronization
This paper evaluates feature extraction techniques in aspect of watermark synchronization. Most watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. The process of synchronizing the location for watermark insertion and detection is crucial to design robust watermarking. One solution for watermark synchronization is to use features. This paper reviews feature extraction techniques in feature-based watermarking: the Harris corner detector and the Mexican Hat wavelet scale interaction method. We evaluate the scale-invariant keypoint extractor in comparison with others. After feature extraction, the set of triangles is generated by Delaunay tessellation. These triangles are the location for watermarking. Redetection ratio of triangles is measured against geometric distortion attacks and signal processing attacks. Experimental results show that the scale–invariant keypoint extractor is appropriate for robust watermarking.
35319384
Gesture spotting from continuous hand motion
This paper proposes a new method of gesture spotting based on the Hidden Markov Model (HMM) that extracts meaningful gestures from continuous hand motion. To remove non-gesture patterns from input patterns, we introduce the threshold model that calculates the threshold likelihood of the input pattern and helps to qualify an input pattern as a gesture. The proposed method extracts gestures with 93.38% reliability.
30313812
A flexible agent system for change adaptation in supply chains
The importance of supply chain management is increasing with globalization and the advancement of electronic business. Supply chains are dynamic due to frequent changes in suppliers, customers, and products. However, information systems for supply chains are not flexible enough to adapt to the changes, requiring high cost and time for re-implementation and re-customization. This paper suggests a flexible agent system for supply chains that can adapt to the changes in transactions introduced by new products or new trading partners. The flexible agent system consists of an interpretable conversation policy model, a procedure for exchanging new conversation policies, and a mechanism for actual transactions with newly acquired conversation policies. By using the flexible agent system, formation of supply chains becomes more robust to the dynamic changes. To show how the approach can be realized, a PC supply chain application is illustrated with a prototype agent platform.
15685762
Why gulling software colleagues is popular
A few months ago, a 550-person software company in Oregon cut a significant part of its developer workforce to reduce expenses and align its salaries with industry averages. It had already streamlined its software development practices, which increased productivity and improved product reliability. During the year-long streamlining program, the company had mapped existing processes to make explicit exactly how software was being developed and then carefully refined the processes to reduce the cost and time required. Implementing these changes required people to relocate into multidisciplinary teams and eliminate tasks that added no value. The majority of staff, facilitated by consultants, participated in this process. At the end of these initiatives, our research team did a follow-up survey and investigation to gauge how well the company was now organized to let staff attain their corporate goals. We found room for more improvement, but also some interesting results regarding employees' attitudes toward staff reductions.
15518000
MediAssist: Using Content-Based Analysis and Context to Manage Personal Photo Collections
We present work which organises personal digital photo collections based on contextual information, such as time and location, combined with content-based analysis such as face detection and other feature detectors. The MediAssist demonstration system illustrates the results of our research into digital photo management, showing how a combination of automatically extracted context and content-based information, together with user annotation, facilitates efficient searching of personal photo collections.
7431488
An HMM-Based Threshold Model Approach for Gesture Recognition
A new method is developed using the hidden Markov model (HMM) based technique. To handle nongesture patterns, we introduce the concept of a threshold model that calculates the likelihood threshold of an input pattern and provides a confirmation mechanism for the provisionally matched gesture patterns. The threshold model is a weak model for all trained gestures in the sense that its likelihood is smaller than that of the dedicated gesture model for a given gesture. Consequently, the likelihood can be used as an adaptive threshold for selecting proper gesture model. It has, however, a large number of states and needs to be reduced because the threshold model is constructed by collecting the states of all gesture models in the system. To overcome this problem, the states with similar probability distributions are merged, utilizing the relative entropy measure. Experimental results show that the proposed method can successfully extract trained gestures from continuous hand motion with 93.14% reliability.