Plants Images Classification Based on Textural Features using Combined Classifier

نویسنده

  • M. Z. Rashad
چکیده

Image classification plays an important role in many applicable fields in our life, such as image analysis, remote sensing, and pattern recognition [9]. It can be defined as the process of sorting all the pixels in an image into a finite number of individual classes[5]. There are many types of techniques which can be used to classify and recognize different types of objects in images. For conventional statistical approaches for land cover classification, they only use the gray values of the image to detect and classify objects. They lead to misclassification due to the strictly convex boundaries. The textural features can be included for better classification but they are inconvenient for the conventional methods. On the other hand, artificial neural networks (ANNs) can handle non-convex decisions [6]. The uses of textural features help to resolve misclassification.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On the use of Textural Features and Neural Networks for Leaf Recognition

for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...

متن کامل

Identification of Houseplants Using Neuro-vision Based Multi-stage Classification System

In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

متن کامل

Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images

Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...

متن کامل

Integrating Textural and Spectral Features to Classify Silicate-Bearing Rocks Using Landsat 8 Data

Texture as a measure of spatial features has been useful as supplementary information to improve image classification in many areas of research fields. This study focuses on assessing the ability of different textural vectors and their combinations to aid spectral features in the classification of silicate rocks. Texture images were calculated from Landsat 8 imagery using a fractal dimension me...

متن کامل

Two New Methods of Boundary Correction for Classifying Textural Images

With the growth of technology, supervising systems are increasingly replacing humans in military, transportation, medical, spatial, and other industries. Among these systems are machine vision systems which are based on image processing and analysis. One of the important tasks of image processing is classification of images into desirable categories for the identification of objects or their sp...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011