Adult Image Content Classification Using Global Features and Skin Region Detection
نویسندگان
چکیده
A method for adult content classification and nudity detection is presented. Objective of this method is to classify images into different classes, varying on the degree of adult content. We utilize MPEG-7 descriptors to represent visual information. Skin regions are detected to model adult content more precisely, as well as to eliminate false-positives. Proposed method is tested with conventional image sets. Experimental results indicate that the algorithm has an acceptable detection performance.
منابع مشابه
A New Skin Detection Approach for Adult Image Identification
With rapid proliferation of adult content on the internet, development of software to detect and filter this content is gaining more and more attention. In this study, a new method for adult image identification is proposed. Accurate human skin detection and extraction of relative features are the bottlenecks in this regard. In the proposed skin detection method, first, Hue color information is...
متن کاملDetermining Effective Features for Face Detection Using a Hybrid Feature Approach
Detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. In this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (MLP) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملRice Classification and Quality Detection Based on Sparse Coding Technique
Classification of various rice types and determination of its quality is a major issue in the scientific and commercial fields associated with modern agriculture. In recent years, various image processing techniques are used to identify different types of agricultural products. There are also various color and texture-based features in order to achieve the desired results in this area. In this ...
متن کامل