Indoor versus Outdoor Scene Classification Using Probabilistic Neural Network
نویسندگان
چکیده
منابع مشابه
Indoor versus Outdoor Scene Classification Using Probabilistic Neural Network
We propose a method for indoor versus outdoor scene classification using a probabilistic neural network (PNN). The scene is initially segmented (unsupervised) using fuzzy C-means clustering (FCM) and features based on color, texture, and shape are extracted from each of the image segments. The image is thus represented by a feature set, with a separate feature vector for each image segment. As ...
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Over the last few years the interest in the research problem of indoor vs. outdoor scene classification[2] has grown significantly, due to its importance in many applications such as Content Based Image Retrieval (CBIR) or Query by Image Content (QBIC), image data organization, robotics, and photography, thus providing a strong motivation for this project. For an example, knowledge of a scene t...
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In this paper, we present a method to classify real-world digital images into indoor and outdoor scenes. Indoor class consists of four groups: bedroom, kitchen, laboratory and library. Outdoor class consists of four groups: landscape, roads, buildings and garden. Application considers real-time system and has a dedicated data-set. Input images are pre-processed and converted into gray-scale and...
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Prior research in scene classification has shown that high-level information can be inferred from low-level image features. Classification rates of roughly 90% have been reported using low-level features to predict indoor scenes vs. outdoor scenes. However, the high classification rates are often achieved by using computationally expensive, high-dimensional feature sets, thus limiting the pract...
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A rapid diffusion of stereoscopic image acquisition devices is expected in the next years. Among the different potential applications that depth information can enable, in this paper we focus on its exploitation as a novel information source in the task of scene classification, and in particular to discriminate between indoor and outdoor images. This issue has not been addressed so far in the l...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2006
ISSN: 1687-6180
DOI: 10.1155/2007/94298