Attribute-based facial image retrieval has wide range of applications, such as in law enforcement, online social networks, etc. The problem becomes more challenging if the images are from different modalities. For exa...
详细信息
ISBN:
(纸本)9781467385640
Attribute-based facial image retrieval has wide range of applications, such as in law enforcement, online social networks, etc. The problem becomes more challenging if the images are from different modalities. For example, the input is a sketch or a composite image, and the task is to retrieve photo images which have the same facial attributes as the input data. In this work, we propose a learning-based approach, in which two transformations are learnt to transform the training images from the two modalities with associated attribute annotations such that images which have similar attributes move closer to each other, and images with very different attributes move farther from each other in the transformed space. Given a query image, it is first transformed to the learnt space in which the images with similar attributes are retrieved. The same framework works seamlessly if the images to be retrieved are of same or different modality as compared to the query data. The attributes of the query image are also automatically obtained as a byproduct of the algorithm. Extensive experimental evaluation on three datasets shows the effectiveness of the proposed approach.
Specular reflection of light degrades the quality of scene images. Whenever specular reflection affects the text portion of such an image, its readability is reduced significantly. Consequently, it becomes difficult f...
详细信息
ISBN:
(纸本)9781479915880
Specular reflection of light degrades the quality of scene images. Whenever specular reflection affects the text portion of such an image, its readability is reduced significantly. Consequently, it becomes difficult for an OCR software to detect and recognize similar texts. In the present work, we propose a novel but simple technique to enhance the region of the image with specular reflection. The pixels with specular reflection were identified in YUV color plane. In the next step, it enhances the region by interpolating possible pixel values in YUV space. The proposed method has been compared against a few existing general purpose image enhancement techniques which include (i) histogram equalization, (ii) gamma correction and (iii) Laplacian filter based enhancement method. The proposed approach has been tested on some images from ICDAR 2003 Robust Reading Competition image database. We computed a Mean Opinion Score based measure to show that the proposed method outperforms the existing enhancement techniques for enhancement of readability of texts in images affected by specular reflection.
Wavelet transform of the image generates the different components basically classified in the approximation and detail components. The approximation component has major information. In this paper a partial encryption ...
详细信息
ISBN:
(纸本)9781467385640
Wavelet transform of the image generates the different components basically classified in the approximation and detail components. The approximation component has major information. In this paper a partial encryption technique is used, using only approximation component. In this paper a random array is generated which is XORed with the approximation component. The inverse transform of the matrix generated by this operation generates the encrypted image. The random array, the wavelet used and level of wavelet transform jointly serves as the key for the decryption process. In decryption is just reverse of the encryption steps.
In this paper, a multi-view stereo image watermarking scheme is proposed to resist the RST (rotation, scaling and translation) attack. To make the scheme resilient to RST, the coefficients of Singular Value Decomposit...
详细信息
ISBN:
(纸本)9781467385640
In this paper, a multi-view stereo image watermarking scheme is proposed to resist the RST (rotation, scaling and translation) attack. To make the scheme resilient to RST, the coefficients of Singular Value Decomposition (SVD) from both left and right views have been used for insertion of the watermark bits. 2D-DWT (Discrete wavelet transform) is used as a preprocessing step to get more correlated SVD coefficients of the left and right view such that the visual degradation due to embedding can be reduced. In this work, a blind embedding scheme is proposed by altering the selected SVD coefficients to improve the robustness of the embedding scheme. A comprehensive set of experiments have been performed to justify the robustness of the proposed scheme against RST attack. Moreover, this scheme can be used to detect the view swapping attack using DIBR technique.
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...
详细信息
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.
We propose algorithms to extract groups of meaningful image level lines using Helmholtz perception principle. In this paper, the meaningfulness refers to the segmentation of circular and rectangular shapes in an image...
详细信息
ISBN:
(纸本)9781424442195
We propose algorithms to extract groups of meaningful image level lines using Helmholtz perception principle. In this paper, the meaningfulness refers to the segmentation of circular and rectangular shapes in an image. We propose an objective assessment of meaningfulness of an image level line when the level line takes the shape of circle or rectangular segment. We have shown that a logical threshold in the meaningfulness value segments images from a variety of applications.
This paper investigates a novel motion vector outlier rejection method based on using mean shift clustering on block motion vectors. The accuracy of compressed domain global motion estimation techniques is largely inf...
详细信息
ISBN:
(纸本)9781479915880
This paper investigates a novel motion vector outlier rejection method based on using mean shift clustering on block motion vectors. The accuracy of compressed domain global motion estimation techniques is largely influenced by its ability to counter the outlier motion vectors. These outliers occur in the block motion vector field due to moving objects, noise or due to large matching errors as a result of the encoders priority on rate distortion optimization. In the present work it is shown that by using mean shift clustering on block motion vectors, those clusters which correspond to outlier motion vectors can be identified. Once detected these clusters are kept out of the global motion estimation process thereby increasing the robustness of estimated camera parameters. The proposed method is compared with existing state-of-the-art outlier removal methods using synthetic and real video sequences to establish and validate its superiority.
Bottom-up saliency detection algorithms identify distinct regions in an image, with rare occurrence of local feature distributions. Notable among those works published recently, use local and global contrast, spectral...
详细信息
ISBN:
(纸本)9781479915880
Bottom-up saliency detection algorithms identify distinct regions in an image, with rare occurrence of local feature distributions. Notable among those works published recently, use local and global contrast, spectral analysis of the entire image or graph based feature mapping. Whereas, we propose a novel unsupervised method using color compactness and statistical modeling of the background cues, to segment the salient foreground region and thus the salient object. At the first stage of processing, the image is segmented into clusters using color feature. First component proposed for our saliency measure combines disparity in color and spatial distance between patches. In addition to rarity of feature, we propose another component for saliency computation that estimates the divergence of the color of a patch from those in the set of patches at the boundary of the image, representing the background. Combination of these two complementary components provides a much improved saliency map for salient object detection. We verify the performance of our proposed method of saliency detection on two popular benchmark datasets, with one or more salient regions and diverse saliency characteristics. Experimental results show that our method outperforms many existing state-of-the-art methods.
Automatic number plate recognition(ANPR) techniques occupy a significant role in intelligent traffic management systems. Most of the existing ANPR systems do not perform well under conditions like high vehicle speed, ...
详细信息
ISBN:
(纸本)9781479915880
Automatic number plate recognition(ANPR) techniques occupy a significant role in intelligent traffic management systems. Most of the existing ANPR systems do not perform well under conditions like high vehicle speed, varying illuminations, changing back ground etc. In this paper we propose an ANPR technique which efficiently solves the above issues using the stroke width transform. In our method, first we pre-process the image to remove blurring artifacts. Then the significant edges in the image are detected and a new image is formed by grouping the connecting rays. This is followed by morphological processing which detects the letters in the image. Then an appropriate Optical Character Recognizer (OCR) recovers the final result. Experimental results show that the proposed method work effectively under varying light conditions and even in the presence of shadows.
Human face anthropometric measurements are used in forensics, orthodontics, face modelling and many other domains, wherein distance between set of facial landmarks play an important role to make inferences. 3D facial ...
详细信息
ISBN:
(纸本)9781467385640
Human face anthropometric measurements are used in forensics, orthodontics, face modelling and many other domains, wherein distance between set of facial landmarks play an important role to make inferences. 3D facial data captured using specialized acquisition methods can be used to reduce the time and tedious task involved in order to compute these measurements. The proposed method is developed to compute fifteen canonical linear measurements between facial landmarks using Kinect camera. Results obtained from this system are compared with the traditional method of measurement using digital Vernier caliper. The experimental results indicate that measurements using RGB-D data obtained from Kinect are good enough for a quick preliminary assessment of the subject as compared to traditional method.
暂无评论