881 resultados para distinctness of image


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This paper presents an overview of our demonstration of a low-bandwidth, wireless camera network where image compression is undertaken at each node. We briefly introduce the Fleck hardware platform we have developed as well as describe the image compression algorithm which runs on individual nodes. The demo will show real-time image data coming back to base as individual camera nodes are added to the network. Copyright 2007 ACM.

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This paper is concerned with choosing image features for image based visual servo control and how this choice influences the closed-loop dynamics of the system. In prior work, image features tend to be chosen on the basis of image processing simplicity and noise sensitivity. In this paper we show that the choice of feature directly influences the closed-loop dynamics in task-space. We focus on the depth axis control of a visual servo system and compare analytically various approaches that have been reported recently in the literature. The theoretical predictions are verified by experiment.

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Multiresolution techniques are being extensively used in signal processing literature. This paper has two parts, in the first part we derive a relationship between the general degradation model (Y=BX+W) at coarse and fine resolutions. In the second part we develop a signal restoration scheme in a multiresolution framework and demonstrate through experiments that the knowledge of the relationship between the degradation model at different resolutions helps in obtaining computationally efficient restoration scheme.

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Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

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We address the problem of face recognition on video by employing the recently proposed probabilistic linear discrimi-nant analysis (PLDA). The PLDA has been shown to be robust against pose and expression in image-based face recognition. In this research, the method is extended and applied to video where image set to image set matching is performed. We investigate two approaches of computing similarities between image sets using the PLDA: the closest pair approach and the holistic sets approach. To better model face appearances in video, we also propose the heteroscedastic version of the PLDA which learns the within-class covariance of each individual separately. Our experi-ments on the VidTIMIT and Honda datasets show that the combination of the heteroscedastic PLDA and the closest pair approach achieves the best performance.

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While researchers strive to improve automatic face recognition performance, the relationship between image resolution and face recognition performance has not received much attention. This relationship is examined systematically and a framework is developed such that results from super-resolution techniques can be compared. Three super-resolution techniques are compared with the Eigenface and Elastic Bunch Graph Matching face recognition engines. Parameter ranges over which these techniques provide better recognition performance than interpolated images is determined.

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Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

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tRNA isolated from . grown in a medium containing [75Se] sodium selenosulfate was converted to nucleosides and analysed for selenonucleosides on a phosphocellulose column. Upon chromatography of the nucleosides on phosphocellulose column, the radioactivity resolved into three peaks. The first peak consisted of free selenium and traces of undigested nucleotides. The second peak was identified as 4-selenouridine by co-chromatographing with an authentic sample of 4-selenouridine. The identity of the third peak was not established. The second and third peaks represented 93% and 7% of the selenium present in nucleosides respectively.

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An inducible Image -mandelate-4-hydroxylase has been partially purified from crude extracts of Pseudomonas convexa. This enzyme catalyzed the hydroxylation of Image -mandelic acid to 4-hydroxymandelic acid. It required tetrahydropteridine, NADPH, Fe2+, and O2 for its activity. The approximate molecular weight of the enzyme was assessed as 91,000 by gel filtration on Sephadex G-150. The enzyme was optimally active at pH 5.4 and 38 °C. A classical Michaelis-Menten kinetic pattern was observed with Image -mandelate, NADPH, and ferrous sulfate and Km values for these substrates were found to be 1 × 10−4, 1.9 × 10−4, and 4.7 × 10−5 Image , respectively. The enzyme is very specific for Image -mandelate as substrate. Thiol inhibitors inhibited the enzyme reaction, indicating that the sulfhydryl groups may be essential for the enzyme action. Treatment of the partially purified enzyme with denaturing agents inactivated the enzyme.

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The antitumor activity of Image -asparagine amidohydrolases (EC 3.5.1.1) from Mycobacterium tuberculosis H37Rv and H37Ra strains has been tested on Yoshida ascites sarcoma in rats. The enzyme specific to M. tuberculosis H37Ra but not to H37Rv has proved to be effective in inhibiting the growth of the sarcoma. Comparative studies on the activity of this enzyme with that of similar enzyme from Escherichia coli B, has shown that at the same levels the former is more effective than the latter. Long-lived immunity to this tumor in A/IISc Wistar rats following treatment of tumor bearing animals with M. tuberculosis H37Ra, pH 9.6 Image -asparaginase has been observed. Immunity in these rats was demonstrated by tumor rejection and detection of humoral antibodies in the sera to the antigen of the cell-free extract of the tumor. The enzyme was ineffective in inhibiting fibrosarcoma in mice at the dose levels tested.

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tRNA isolated from Image Image , grown in the presence of radioactive sulfur was analyzed for the occurrence of thionucleotides. The analysis revealed the presence of at least five thionucleotides, of which three were identified as 4-thiouridylic acid, 5-methylaminomethyl-2-thiouridylic acid and 2-thiocytidylic acid. Iodine-oxidation affected the acceptor ability of several amino acid specific tRNAs, those for lysine and serine being affected most. The tRNA of Image Image differs from that of Image . Image both in the number and the relative proportion of thionucleotides.

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Purpose This paper takes a customer view on corporate image and value, and discusses the value of image in service. We propose a model depicting how the customer’s corporate brand image affects the customer’s value-in-use. Methodology/approach The paper represents conceptual development on customers’ value and image construction processes. By integrating ideas and elements from the current service and branding literature a model is proposed that extends current views on how value-in-use emerges. Findings From a current service perspective it is the customer who makes value assessments when experiencing service. Similarly, if branding is a concept used to denote the service provider’s intentions and attempts to create a corporate brand, image construction is the corresponding process where the customer constructs the corporate image. This image construction process is always present both in service interactions and in communication and has an effect on the customer’s value-in-use. We argue that two interrelated concepts are needed to capture corporate image construction and dynamics and value-in-use – the image-in-use and image heritage. Research implications The model integrates two different streams of research pointing to the need to consider traditional marketing communication and service interactions as inherently related to each other from the customer’s point of view. Additionally the model gives a platform for understanding how value-in-use emerges over time. New methodological approaches and techniques to capture image-in-use and image heritage and their interplay with value-in-use are needed. Practical implications The company may not be able to control the emergence of value-in-use but may influence it, not only in interactions with the customer but also with pure communication. Branding activities should therefore be considered related to service operations and service development. Additionally, practitioners would need to apply qualitative methods to understand the customer’s view on image and value-in-use. Originality/value The paper presents a novel approach for understanding and studying that the customer’s image of a company influences emergence of value-in-use. The model implies that the customer’s corporate image has a crucial role for experienced value-in-use.