دانلود مقاله ISI انگلیسی شماره 79650
عنوان فارسی مقاله

برنامه نویسی ژنتیک دو لایه: به سوی طبقه بندی تصویر مبتنی بر پیکسل خام

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
79650 2012 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Two-Tier genetic programming: towards raw pixel-based image classification
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 39, Issue 16, 15 November 2012, Pages 12291–12301

کلمات کلیدی
محاسبات تکاملی؛ برنامه نویسی ژنتیک؛ استخراج ویژگی؛ انتخاب ویژگی؛ طبقه بندی تصویر
پیش نمایش مقاله
پیش نمایش مقاله برنامه نویسی ژنتیک دو لایه: به سوی طبقه بندی تصویر مبتنی بر پیکسل خام

چکیده انگلیسی

Classifying images is of great importance in machine vision and image analysis applications such as object recognition and face detection. Conventional methods build classifiers based on certain types of image features instead of raw pixels because the dimensionality of raw inputs is often too large. Determining an optimal set of features for a particular task is usually the focus of conventional image classification methods. In this study we propose a Genetic Programming (GP) method by which raw images can be directly fed as the classification inputs. It is named as Two-Tier GP as every classifier evolved by it has two tiers, the other for computing features based on raw pixel input, one for making decisions. Relevant features are expected to be self-constructed by GP along the evolutionary process. This method is compared with feature based image classification by GP and another GP method which also aims to automatically extract image features. Four different classification tasks are used in the comparison, and the results show that the highest accuracies are achieved by Two-Tier GP. Further analysis on the evolved solutions reveals that there are genuine features formulated by the evolved solutions which can classify target images accurately.

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