کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361285 | 870090 | 2015 | 38 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Saliency-driven image classification method based on histogram mining and image score
ترجمه فارسی عنوان
روش طبقه بندی تصور بر اساس معیار بر اساس استخراج هیستوگرام و نمره تصویر
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Since most image classification tasks involve discriminative information (i.e., saliency), this paper proposes a new bag-of-phrase (BoP) approach to incorporate this information. Specifically, saliency map and local features are first extracted from edge-based dense descriptors. These features are represented by histogram and mined with discriminative learning technique. Image score calculated from the saliency map is also investigated to optimize a support vector machine (SVM) classifier. Both feature map and kernel trick methods are explored to enhance the accuracy of the SVM classifier. In addition, novel inter- and intra-class histogram normalization methods are investigated to further boost the performance of the proposed method. Experiments using several publicly available benchmark datasets demonstrate that the proposed method achieves promising classification accuracy and superior performance over state-of-the-art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2567-2580
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2567-2580
نویسندگان
Baiying Lei, Ee-Leng Tan, Siping Chen, Dong Ni, Tianfu Wang,