Several single valued measures have been proposed by researchers for the quantitative performance evaluation of medical image retrieval systems. Precision and recall are the most common evaluation measures used by res...
详细信息
ISBN:
(纸本)9780819498304
Several single valued measures have been proposed by researchers for the quantitative performance evaluation of medical image retrieval systems. Precision and recall are the most common evaluation measures used by researchers. Amongst graphical measures proposed, precision vs. recall graph is the most common evaluation measure. Precision vs. recall graph evaluates different systems by varying the operating points (number of top retrieval considered). However, in real life the operating point for different applications are known. Therefore, it is essential to evaluate different retrieval systems at a particular operating point set by the user. None of the graphical metric provides the variation of performance of query images over the entire database at a particular operating point. This paper proposes a graphical metric called Complementary Cumulative Precision Distribution (CCPD) that evaluates different systems at a particular operating point considering each images in the database for query. The strength of the metric is its ability to represent all these measures pictorially. The proposed metric (CCPD) pictorially represents the different possible values of precision and the fraction of query images at those precision values considering number of top retrievals constant. Different scalar measures are derived from the proposed graphical metric (CCPD) for effective evaluation of retrieval systems. It is also observed that the proposed metric can be used as a tie breaker when the performance of different methods are very close to each other in terms of average precision.
In this work, we employ the well-known Hamilton-Jacobi to Schrödinger connection to present a unified framework for computing both the Euclidean distance function and its gradient density in two dimensions. Previ...
详细信息
ISBN:
(纸本)1595930361
In this work, we employ the well-known Hamilton-Jacobi to Schrödinger connection to present a unified framework for computing both the Euclidean distance function and its gradient density in two dimensions. Previous work in this direction considered two different formalisms for independently computing these quantities. While the two formalisms are very closely related, their lack of integration is theoretically troubling and practically cumbersome. We introduce a novel Schrödinger wave function for representing the Euclidean distance transform from a discrete set of points. An approximate distance transform is computed from the magnitude of the wave function while the gradient density is estimated from the Fourier transform of the phase of the wave function. In addition to its simplicity and efficient O(N logN) computation, we prove that the wave function-based density estimator increasingly, closely approximates the distance transform gradient density (as a free parameter approaches zero) with the added benefit of not requiring the true distance function. Copyright 2014 ACM.
Most work on automatic writer identification relies on hand-writing features defined by humans[6, 4]. These features correspond to basic units such as letters and words of text. Instead of relying on human-defined fea...
详细信息
ISBN:
(纸本)1595930361
Most work on automatic writer identification relies on hand-writing features defined by humans[6, 4]. These features correspond to basic units such as letters and words of text. Instead of relying on human-defined features, we consider here the determination of writing similarity using automatically determined word-level features learnt by a deep neural network. We generalize the problem of writer identification to the definition of a content-irrelevant handwriting similarity. Our method first takes whether two words were written by the same person as a discriminative label for word-level feature training. Then, based on word-level features, we define writing similarity between passages. This similarity not only shows the distinction between writing styles of different people, but also the development of style of the same person. Performance with several hidden layers in the neural network are evaluated. The method is applied to determine how a person's writing style changes with time considering a children's writing dataset. The children's handwriting data are annually collected. They were written by children of 2nd, 3rd or 4th grade. Results are given with a whole passage (50 words) of writing over one-year change. As a comparison, similar experiments on a small amount of data using conventional generative model are also given. Copyright 2014 ACM.
This paper presents a novel emotion recognition model using the system identification approach. A comprehensive data driven model using an extended Kohonen self-organizing map (KSOM) has been developed whose input is ...
详细信息
In all imageprocessing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environm...
详细信息
ISBN:
(纸本)9781479915880
In all imageprocessing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environment. Thus, it is essential to enhance the clarity of the image by some post-processing techniques. image deblurring is one of such techniques to remove the blurry effect of the captured image. This paper looks into this problem in a different way, where the deblurring of an image is addressed by solving image super-resolution problem. The blurred image is first down-sampled and then it is fed to the super-resolution framework to produce the deblurred high resolution image. In addition, the proposed approach states the requirement of edge preservation in the problem. The experimental results are comparable with the existing image deblurring algorithms.
One of the foremost requisite for human perception and computervision task is to get an image with all objects in focus. The image fusion process, as one of the solutions, allows getting a clear fused image from seve...
详细信息
ISBN:
(纸本)9781479915880
One of the foremost requisite for human perception and computervision task is to get an image with all objects in focus. The image fusion process, as one of the solutions, allows getting a clear fused image from several images acquired with different focus levels of a scene. In this paper, a novel framework for multi-focus image fusion is proposed, which is computationally simple since it realizes only in the spatial domain. The proposed framework is based on the fractal dimensions of the images into the fusion process. The extensive experiments on different multifocus image sets demonstrate that it is consistently superior to the conventional image fusion methods in terms of visual and quantitative evaluations.
This paper presents an implementation of an OCR system for the Meetei Mayek script. The script has been newly reintroduced and there is a growing set of documents currently available in this script. Our system accepts...
详细信息
ISBN:
(纸本)9781479915880
This paper presents an implementation of an OCR system for the Meetei Mayek script. The script has been newly reintroduced and there is a growing set of documents currently available in this script. Our system accepts an image of the textual portion of a page and outputs the text in the Unicode format. It incorporates preprocessing, segmentation and classification stages. However, no post-processing is done to the output. The system achieves an accuracy of about 96% on a moderate database.
Scan time reduction in MRI can be achieved by partial k-space reconstruction. Truncation of the k-space results in generation of artifacts in the reconstructed image. A subspace projection algorithm is developed for a...
详细信息
ISBN:
(纸本)9781479915880
Scan time reduction in MRI can be achieved by partial k-space reconstruction. Truncation of the k-space results in generation of artifacts in the reconstructed image. A subspace projection algorithm is developed for artifact-free reconstruction of sparse MRI. The algorithm is applied to a frequency weighted k-space, which fits into a signal-space model for sparse MR images. The application is illustrated using Magnetic Resonance Angiogram (MRA).
Visual attention is an indispensable component of complex vision tasks. When looking at a complex scene, our ocular perception is confronted with a large amount of data that needs to be broken down for processing by o...
详细信息
ISBN:
(纸本)9781479915880
Visual attention is an indispensable component of complex vision tasks. When looking at a complex scene, our ocular perception is confronted with a large amount of data that needs to be broken down for processing by our psychovisual system. Selective visual attention provides a mechanism for serializing the visual data, allowing for sequential processing of the content of the scene. A Bottom-Up computational model is described that simulates the psycho-visual model of saliency based on features of intensity and color. The method gives sequential priorities to objects which other computational models cannot account for. The results demonstrate a fast execution time, full resolution maps and high detection accuracy. The model is applicable on both natural and artificial images.
暂无评论