Multidimensional Markov Stationary Feature for Image Retrival Systems
نویسندگان
چکیده
منابع مشابه
Adaptive Feature Transformation for Image Data from Non-stationary Processes
This paper introduces the application of the feature transformation approach proposed by Torkkola [1] to the domain of image processing. Thereto, we extended the approach and identifed its advantages and limitations. We compare the results with more common transformation methods like Principal Component Analysis and Linear Discriminant Analysis for a function approximation task from the challen...
متن کاملSemantic Feature Extraction with Multidimensional Hidden Markov Model
Conventional block-based classification is based on the labeling of individual blocks of an image, disregarding any adjacency information. When analyzing a small region of an image, it is sometimes difficult even for a person to tell what the image is about. Hence, the drawback of context-free use of visual features is recognized up front. This paper studies a context-dependant classifier based...
متن کاملUsing Mobile Agents for Information Retrival in B2B Systems
This paper presents an architecture of an information retrieval system that use the advantages offered by mobile agents to collect information from different sources and bring the result to the calling user. Mobile agent technology will be used for determine the traceability of a product and also for searching information about a specific entity.
متن کاملUnsupervised Non Stationary Image Segmentation Using Triplet Markov Chains
This work deals with the unsupervised Bayesian hidden Markov chain restoration extended to the non stationary case. Unsupervised restoration based on “ExpectationMaximization” (EM) or “Stochastic EM” (SEM) estimates considering the “Hidden Markov Chain” (HMC) model is quite efficient when the hidden chain is stationary. However, when the latter is not stationary, the unsupervised restoration re...
متن کاملMultidimensional Hidden Markov Model Applied to Image and Video Analysis
Recent progress and prospects in cognitive vision, multimedia, human-computer interaction, communications and the Web call for, and can profit from applications of advanced image and video analysis. Adaptive robust systems are required for analysis , indexing and summarization of large amounts of audiovisual data. Image classification is perhaps the most important part of digital image analysis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Rajshahi University Journal of Science and Engineering
سال: 2016
ISSN: 2408-8803,2309-0952
DOI: 10.3329/rujse.v44i0.30396