The main aim of the present study was to map of Urmia Lake water surface diminishing rates over a long-term period, and demonstrating the most recent surface of emerged salty alluvial plains. For this purpose, Landsat TM, ETM+ and OLI imageries, observing from 1984 to 2015, were progressively processed to generate most of the thematic models in tempo-spatial context. All multi-date satellite da...

Automatic identification of insects and diseases has attracted researchers for the last few years. Researchers have suggested several algorithms to get around problems manually identifying pests. Image processing techniques deep convolution neural networks can overcome challenges manual insect classification. This work focused on optimizing assessing convolutional identification. AlexNet, Mobil...

counting the population of insect pests is a key task for planning a successful integrated pest management program. most image processing and machine vision techniques in the literature are very site-specific and cannot be easily re-usable because their performances are highly related to their ground truth data. in this article a new unsupervised image processing method is proposed which is gen...

Primary challenges are the identification, segmentation, and extraction of afflicted area from scanning magnetic resonance. However, it is a time-consuming tiresome for clinical specialists. In this paper, an automated brain tumor system proposed. The proposed employs hybrid image processing techniques such as contrast correction, histogram normalization, thresholding techniques, arithmetic, mo...

ABSTRACT- The evaluation of leaf area and leaf nutritional value is important for crop growth modeling and estimations of its performance. The purpose of this study was to use image processing techniques to develop an economical method to ease the assessment of nutrient status and leaf area (LA) of plants and to compare the outcomes of this method with linear models. Leaf area and leaf chloroph...

In this study based on image analysis, an ore grade estimation model was developed. The study was performed at a limestone mine in central Iran. The samples were collected from different parts of the mine and crushed in size from 2.58 cm down to 15 cm. The images of the samples were taken in appropriate environment and processed. A total of 76 features were extracted from the identified rock sa...