Plant Classification in Images of Natural Scenes Using Segmentations Fusion
نویسندگان
چکیده مقاله:
This paper presents a novel approach to automatic classifying and identifying of tree leaves using image segmentation fusion. With the development of mobile devices and remote access, automatic plant identification in images taken in natural scenes has received much attention. Image segmentation plays a key role in most plant identification methods, especially in complex background images. Where there are no presumptions about leaf and background, segmentation of leaves in images with complex background is very difficult. In addition, each image has special conditions, so parameters of the algorithm must be set for each image. In this paper, image segmentation fusion is used to overcome this problem. A fast method based on maximum mutual information is used to fuse the results of leaf segmentation algorithms with different parameters. Applying Tsallis entropy and g-calculus, generalized mutual information equations are derived and used to obtain the best consensus segmentation. To evaluate the proposed methods, a dataset with tree leaf images in natural scenes and complex backgrounds is used. These images were taken from Pl@ntLeaves dataset and modified so that they do not have a presumption. The experimental results show the use of Tsallis entropy and g-calculus in image segmentation fusion, improves plant species identification.
منابع مشابه
Nonhomogeneous resolution of images of natural scenes.
The aim of this research is to model and simulate the loss of visual resolution as a function of retinal eccentricity in the perception of natural scenes. The model of visual resolution is based on a space-variant low-pass filter, having a variable convolution kernel according to retinal eccentricity. The parameters of the model are computed from psychophysical measures of visual acuity as a fu...
متن کاملVisual sensitivity to color errors in images of natural scenes.
Simple color-difference formulae and pictorial images have traditionally been used to estimate the visual impact of color errors introduced by image-reproduction processes. But the limited gamut of RGB cameras constrains such analyses, particularly of natural scenes. The purpose of this work was to estimate visual sensitivity to color errors introduced deliberately into pictures synthesized fro...
متن کاملImproving Text Recognition in Images of Natural Scenes
IMPROVING TEXT RECOGNITION IN IMAGES OF NATURAL SCENES
متن کاملClassification of Ultra-high Resolution Images using Soft Computing
The main objective of this paper is to use a computational intelligence algorithm for preparing a mapping map that categorizes different patterns of identification of infected areas and changes in radiation pollution. In this paper, the use of the fuzzy inference system has been proposed to determine the degree of radiation contamination in the regions. The study uses ultra-high resolution spec...
متن کاملInferring Depth from Single Images in Natural Scenes
The inverse optics problem is one of the oldest and most well known problems in visual perception. Inferring the underlying sources of visual images has no analytic solution. Recent work on brightness, color, and form has suggested that visual percepts represent the probable sources of visual stimuli and not the stimuli as such, suggesting an empirical theory of visual perception. Here I explor...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 33 شماره 9
صفحات 1743- 1750
تاریخ انتشار 2020-09-01
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023