A tamper detection suitable fragile watermarking scheme based on novel payload embedding strategy

Multimedia Tools and Applications - Intentional tampering in digital image content is one of the common malpractices in the current digital arena. So in this paper, the authors have proposed a...     

PRATIT: a CNN-based emotion recognition system using histogram equalization and data augmentation

Multimedia Tools and Applications - Emotions are spontaneous feelings that are accompanied by fluctuations in facial muscles, which leads to facial expressions. Categorization of these facial...     

Image retrieval based on AND/OR-construction models

With the rapid development of the Internet, finding desired images from numerous images has become an important research topic. In this paper, we propose an image retrieval system facilitating retrieval time and accuracy. Since the performance of image retrieval is deeply influenced by image features and retrieval methods. Five different types of features and five different methods are used to find the best combination for an image retrieval system. First, we segment out the main object in an image and then extract its features. Next, relevant features are selected from the original feature set for facilitating image retrieval, using the SAHS algorithm. Then, five methods based on AND/OR-construction are proposed to build the image retrieval model, using the relevant features. Finally, the experimental results not only show that our methods are more effective than the other state-of-the-art methods but also present some observations never explored by the previous research.

     

An airlight estimation method for image dehazing based on gray projection

Multimedia Tools and Applications - As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic...     

Preserving interactions among moving objects in surveillance video synopsis

Video synopsis is an effective solution for fast browsing and retrieval of long surveillance videos. It aims to shorten long video sequences into its equivalent compact video representation by rearranging the video events in the temporal domain and/or spatial domain. Conventional video synopsis methods focus on reducing the collisions between tubes and maintaining their chronological order, which may alter the original interactions between tubes due to improper tube rearrangement. In this paper, we present an approach to preserve the relationships among tubes (tracks of moving objects) of the original video in the synopsis video. First, a recursive tube-grouping algorithm is proposed to determine the behavior interactions among tubes in a video and group the related tubes together to form tube sets. Second, to preserve the discovered relationships, a spatio-temporal cube voting algorithm is proposed. This cube voting method optimally rearranges the tube sets in the synopsis video, minimizing false collisions between tubes. Third, a method to estimate the duration of the synopsis video is proposed based on an entropy measure of tube collisions. The extensive experimental results demonstrate that the proposed video synopsis framework condenses videos by preserving the original tube interactions and reducing false tube collisions.

     

Local jet pattern: a robust descriptor for texture classification

Multimedia Tools and Applications - Methods based on locally encoded image features have recently become popular for texture classification tasks, particularly in the existence of large intra-class...     

Smartphone-based bulky waste classification using convolutional neural networks

Multimedia Tools and Applications - The rapid urbanization process is escalating the urban waste problem, and ineffective management has worsened the issue, leading to severe consequences to the...     

Violence detection in videos for an intelligent surveillance system using MoBSIFT and movement filtering algorithm

Pattern Analysis and Applications - Action recognition is an active research area in computer vision as it has enormous applications in today’s world, out of which, recognizing violent action...     

Rare association rule mining from incremental databases

Pattern Analysis and Applications - Rare association rule mining is an imperative field of data mining that attempts to identify rare correlations among the items in a database. Although numerous...