Semantic Concepts Classification on Outdoor Scene Images Based on Region - Based Approach
نویسنده
چکیده
Outdoor scene analysis is a complex problem for both image processing and pattern recognition domains. There are two methods of segmenting images to look for objects in an image, block-based and region-based. Region-based method can provide some useful information about objects even though segmentation may not be perfect. There are three phases in this system: segmentation, features extraction and classification. The basic idea of this system is to classify local image regions into semantic concept classes such as tree, sky and road etc. In this paper, modified Marker-Controlled Watershed (MCWS) algorithm is proposed. Firstly, the modified (MCWS) algorithm is used to segment input image. And then, texture feature vectors are extracted from segmented regions by Gray-Level Co-occurrence Matrix (GLCM). Finally, classification is performed by 3-layer Artificial Neural Network (ANN). This system is applied on real scene images dataset.
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