شماره ركورد كنفرانس :
1730
عنوان مقاله :
Objective Evaluation of Image Segmentation Algorithms Using Neural Network
عنوان به زبان ديگر :
Objective Evaluation of Image Segmentation Algorithms Using Neural Network
پديدآورندگان :
Askari Elham نويسنده , Eftekhari Moghadam Amir Masoud نويسنده , Rashidy Kanan Hamidreza نويسنده
تعداد صفحه :
6
كليدواژه :
Objective evaluation , neural network , image segmentation , Over-segmentation , important feature
سال انتشار :
2012
عنوان كنفرانس :
بيستمين كنفرانس مهندسي برق ايران
زبان مدرك :
فارسی
چكيده لاتين :
Image segmentation is an important research area in computer vision and many image segmentation methods have been proposed, therefore it is necessary to be able to evaluate theperformance of image segmentation algorithms objectively. In this paper we present a new metric to evaluate the accuracy ofimage segmentation algorithms, based on the most important feature of each segments using neural networks. The neural network after training can assess the similarity or dissimilarity of each pairs of segments, based on the most important feature of two segments that can be distinguished from each other andfinally the segmentation algorithms accuracy have been computed by novel presented metric. Our proposed method donot require a manually-segmented reference image for comparison, therefore can be used for real-time evaluation and is sensitive to over-segmentation. Experimental results were obtained for a selection of images from Berkeley segmentation data set and demonstrated that it’s a proper measure for comparing image segmentation algorithms
شماره مدرك كنفرانس :
4460809
سال انتشار :
2012
از صفحه :
1
تا صفحه :
6
سال انتشار :
2012
لينک به اين مدرک :
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