A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Gumaste, S. V.
- Automatic Graph Based Clustering for Image Searching and Retrieval from Database
Authors
1 Dept. of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology Lohegaon, Pune, IN
2 Dept. of Computer Engineering, R.H. Chaapte College of Engineering Nashik, IN
Source
Software Engineering, Vol 8, No 2 (2016), Pagination: 39-49Abstract
Content-based image retrieval and searching is one of the most burning issues in the field of multimedia computing. Human perception is not understood well enough to automate the retrieval process. In this work we have designed a system for content-based image searching. This system uses multiple cues (features) for image searching and retrieval. Since most of the features have some drawbacks, we use the cues that are free from drawbacks like geometrical transforms and viewpoint variation. We present the results based on these cues. A heuristic for combining the result of different cues to increase the accuracy of the system is developed. Databases of different size were used to estimate the accuracy of the system. Global shape descriptor of images and object based descriptors are extracted for the retrieval of images. Multimedia databases are very big in size, so we cannot go for exhaustive searching of images from these databases. For this purpose an automatic graph-based clustering algorithm is developed to reduce the searching time of the images from the database. The proposed algorithm works on the concept of minimum spanning tree that removes the inconsistent edges from tree, based on the dynamic threshold provided to the algorithm. The proposed algorithm reduces the search time for the retrieval without much loss in the accuracy. We found out that careful combination of the different cues, based on our proposed heuristic, can increase the retrieval accuracy up to a noticeable extent.
Keywords
Content-Based Image Retrieval (CBIR), Colour Coherent Vectors (CCV) and Query by Image Content (QBIC).
- Review Paper:Detail Study for Sign Language Recognization Techniques
Authors
1 VTU, Belgaum, Karnataka, IN
2 Department of Computer Engg, R. H. Sapat College of Engineering, Nashik, Pune, Maharashtra, IN
Source
Digital Image Processing, Vol 8, No 3 (2016), Pagination: 65-69Abstract
This paper reviews the intensive state of the art in automatic recognition of continuous signs, from different languages, supported the information sets used, features computed, technique used, and recognition rates achieved. In this paper discover that, in the past, most work has been tired finger-spelled words and isolated sign recognition, but recently, there has been vital progress within the recognition of signs embedded briefly continuous sentences. Paper tend to conjointly realize that researchers are getting down addressing the necessary downside of extracting and integration non-manual data that is gift in face and head movement and present results from experiments integration of non-manual options.
Keywords
American Sign Language (ASL), Hidden Marko Model (HMM) and Extended Multi Modal Annotation (EMMA).- New Frame Work for Translation of Sign Language Action into Text Description in Kannada
Authors
1 Department of Computer Engineering, Dr. D Y Patil School of Engineering and Technology, Pune, IN
2 Department of Computer Engineering, R. H. Sapat College of Engineering, Nashik, Maharashtra, IN
Source
Digital Image Processing, Vol 8, No 10 (2016), Pagination: 315-319Abstract
In later year's gesture based communication acknowledgment has turned in a standout amongst the most developing fields of examination and it is the most characteristic method of correspondence for the individuals with listening to issues. A hand signal acknowledgment framework can give a chance to hard of hearing persons speak with typical individuals without the need of a translator or middle. Proposed system is going to construct a framework and techniques for the programmed acknowledgment of the Kannada communication via gestures. Through that we are giving instructing classes to the reason for preparing the hard of hearing sign client in Kannada. The framework does oblige hand to be appropriately adjusted to the camera and does not require any wearable sensors. A substantial arrangement of tests has been utilized as a part of the proposed framework to perceive confined words from the standard Kannada communication through signing, which are taken before the camera with distinctive hard of hearing sign client. In proposed framework, we mean to perceive some extremely essential components of gesture based communication and to make an interpretation of them to content and the other way around. The proposed framework utilizing 36 Kannada letters in order for acknowledgment.