The recent era of digitization is expected to digitized many old important documents which are degraded due to various reasons. Degraded document image binarization has many challenges like intensity variation, backgr...
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ISBN:
(纸本)9781467385640
The recent era of digitization is expected to digitized many old important documents which are degraded due to various reasons. Degraded document image binarization has many challenges like intensity variation, background contrast variation, bleed through, text size variation and so on. Many approaches are available for document image binarization, but none can handle all types of degradation at once. We proposed an approach which consists of three stages such as preprocessing, Text-Area detection and post-processing. Preprocessing enhances the contrast of the image. Next stage involves identifying Text-Area. Postprocessing technique takes care of false positives and false negative based on intensity values of preprocessed and gray image. The Performance is evaluated based on various quantitative measures and is compared with the method regarded best so far. The algorithm is also expected to be independent of the script, hence is tested on Gujarati degraded document images.
Segmentation of cell nuclei in PAP-smear cervical images is of preeminent importance in computer-aided-diagnostic screening technique for cervical cancer. This paper proposes a novel nuclei segmentation approach which...
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ISBN:
(纸本)9781467385640
Segmentation of cell nuclei in PAP-smear cervical images is of preeminent importance in computer-aided-diagnostic screening technique for cervical cancer. This paper proposes a novel nuclei segmentation approach which builds upon the mean-shift method. The mean-shift method is applied on the cell images which first undergo a decorrelation-stretch contrast enhancement. The results of mean-shift based approach is refined further using morphological operations. We have validated results of segmentation on dataset which includes 900 images with the given ground truth. We demonstrate that our simple and efficient approach yields high validation rate on a large image dataset. In addition, we also show encouraging visual results on another set of more complex real images.
In this paper we propose a novel real time video sailency detection algorithm based on disorder in Motion Field. The proposed algorithm operates on the basic premise that higher disorder pertains to higher information...
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ISBN:
(纸本)9781467385640
In this paper we propose a novel real time video sailency detection algorithm based on disorder in Motion Field. The proposed algorithm operates on the basic premise that higher disorder pertains to higher information in the scene. Based on the quantified value of the disorder, salient areas in the video frame are demarcated. In order to achieve real time operational capability, the algorithm operates in compressed H.264 domain rather than in pixel domain. The proposed algorithm has been evaluated on standard video sequences and results on real time video surveillance data are also presented.
Human authentication can now be seen as a crucial social problem. In this paper a multimodal authentication system is presented which is highly reliable and fuses iris, finger-knuckleprint and palmprint image matching...
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ISBN:
(纸本)9781467385640
Human authentication can now be seen as a crucial social problem. In this paper a multimodal authentication system is presented which is highly reliable and fuses iris, finger-knuckleprint and palmprint image matching scores. Segmented ROI are preprocessed using DCP (Differential Code Pattern) to obtain robust corner features. Later they are matched using the GOF (Global Optical Flow) based dissimilarity measure. The proposed system has been tested on Casia Interval and Lamp iris, PolyU finger-knuckle-print and PolyU and Casia palmprint, public databases. The proposed system has shown good performance over all unimodal databases while over multimodal (fusion of all three) databases it has shown perfect performance (i:e: CRR = 100% with EER = 0%).
Analysis of a very long video and semantically describe the contents is a challenging task in computervision. The present approaches such as video shot detection and summarization address this problem partially while...
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ISBN:
(纸本)9781467385640
Analysis of a very long video and semantically describe the contents is a challenging task in computervision. The present approaches such as video shot detection and summarization address this problem partially while maintaining the temporal coherency. To reduce the user efforts for seeing the whole video we have introduced a new technique which combines similar content irrespective of their presence at different time instants. In this approach, we automatically identify only the representative frames corresponding to similar scenes which were captured at different instants of time. We also provide the labels of the objects that are present in the representative frames along with the compact representation for the video. We achieve the task of semantic labelling of frames in a unified framework using a deep learning framework involving pre-trained features through a convolutional neural network. We show that the proposed approach is able to address the semantic labelling effectively as justified by the results obtained for videos of different scenes captured through different modalities.
In this paper, a fractional order total variation (TV) model is presented for estimating the optical flow in the image sequences. The proposed fractional order model is introduced by generalizing a variational flow mo...
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ISBN:
(纸本)9781467385640
In this paper, a fractional order total variation (TV) model is presented for estimating the optical flow in the image sequences. The proposed fractional order model is introduced by generalizing a variational flow model formed with a quadratic and a total variation terms. However, it is difficult to solve this generalized model due to the non-differentiability of the total variation regularization term. The Grunwald-Letnikov derivative is used to discretize the fractional order derivative. The resulting formulation is solved by using an efficient numerical algorithm. The experimental results verify that the proposed model yields a dense flow and preserves discontinuities in the flow field. Moreover, It also provides a significant robustness against outliers.
In this paper we represent a new technique to interact with the computer in a non-tangible way. Specifically we have designed a Media Player system controller by Facial Expressions and Gestures (MP-FEG). We detect and...
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ISBN:
(纸本)9781467385640
In this paper we represent a new technique to interact with the computer in a non-tangible way. Specifically we have designed a Media Player system controller by Facial Expressions and Gestures (MP-FEG). We detect and track one landmark point on the finger and 18 landmark points on the lips to capture the movement of the finger and the lips of the user. The movement patterns are classified into hand gestures and facial expressions using support vector machine (SVM). We have achieved similar to 98.65% and similar to 100% recognition accuracies for hand-gestures and facial expressions respectively. Occurrence of each of these actions (5 hand-gesturs and 3 facial expressions) is associated with a command to control (e.g., to select, play, pause the video) the video player. Perceptional quality analysis by user survey rates the experience of the non-tangible human-computer interaction facilited by the proposed technique as 'good'.
We use the RGB-D technology of Kinect to control an application with hand-gestures. We use PowerPoint for test. The system can start/end PPT, navigate between slides, capture or release the control of the cursor, and ...
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ISBN:
(纸本)9781467385640
We use the RGB-D technology of Kinect to control an application with hand-gestures. We use PowerPoint for test. The system can start/end PPT, navigate between slides, capture or release the control of the cursor, and control it through natural gestures. Such a system is useful and hygienic in the kitchen, lavatories, hospital ICUs for touch-less surgery, and the like. The challenge is to extract meaningful gestures from continuous hand motions. We propose a system that recognizes isolated gestures from continuous hand motions for multiple gestures in real-time. Experimental results show that the system has 96.48% precision (at 96.00% recall) and performs better than the Microsoft Gesture Recognition library for swipe gestures.
Instance retrieval (IR) is the problem of retrieving specific instances of a particular object, like a monument, from a collection of images. Currently, the most popular methods for IR use Bag of words (BoW) features ...
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ISBN:
(纸本)9781467385640
Instance retrieval (IR) is the problem of retrieving specific instances of a particular object, like a monument, from a collection of images. Currently, the most popular methods for IR use Bag of words (BoW) features for retrieval. However, a prominent problem for IR remains the tendency of BoW based methods to retrieve near-identical images as most relevant results. In this paper, we define diversity in IR as variation of physical properties among most relevant retrieved results for a query image. To achieve this, we propose both an ITML algorithm that re-fashions the BoW feature space into one that appreciates diversity better, and a measure to evaluate diversity in retrieval results for IR applications. Additionally, we also generate 200 hand-labeled images from the Paris dataset, for use in further research in this area. Experiments on the popular Paris dataset show that our method outperforms the standard BoW model in many cases.
A novel method for face recognition system using challenging profile and frontal faces is proposed in this paper. The proposed face recognition system consists of pre-processing, feature extraction and classification ...
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ISBN:
(纸本)9781467385640
A novel method for face recognition system using challenging profile and frontal faces is proposed in this paper. The proposed face recognition system consists of pre-processing, feature extraction and classification components. In this work, for pre-processing, the face region is extracted using facial landmark points, obtained by the tree structured part model. During feature extraction, SIFT descriptors are computed from the detected face region, and Spatial Pyramid Matching approach based on Locality constraints Linear Coding technique is employed for feature representation. Finally multi-class linear SVM classifier is employed to do the classification job. Extensive experimental results have been performed to show that the proposed algorithm has satisfying performance as compared to existing methods for IITK, CASIA-FACE-V5, LIBOR, ORL and Extended YALE-B face databases.
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