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In this paper, we investigate the use of neural networks (NN) to detect weed plants in rice fields based on aerial images. For this purpose, images are taken at 50 meters high with 16.1 megapixels CMOS digital camera mount-ted on an autonomous electrical fixed wind plane. Then, an ortho-mosaic map of the field is created by stitching 250 pictures, as the image is ortho-corrected, the pixel information...
This paper presents an accurate and automatic algorithm to recognize and count fish in the video footages of fishery operations. The unique character of the approach is that it combines machine learning techniques with statistical methods to fully make use the benefits of these algorithms. The approach consists of three major stages including video data preparation such as noise deduction, preliminary...
Tongue color recognition is one of important research in objective tongue diagnosis. Since the network structure of traditional BP-ANN can greatly affect the recognition rates of tongue color, a kind of improved BP-ANN with self-adaptive network structure is introduced to solve the problem of tongue color recognition. In this method, according to the recognition rates, the node number of the hidden...
Now-a-days as there is prohibitive demand for agricultural industry, effective growth and improved yield of fruit is necessary and important. For this purpose farmers need manual monitoring of fruits from harvest till its progress period. But manual monitoring will not give satisfactory result all the times and they always need satisfactory advice from expert. So it requires proposing an efficient...
In this paper, artificial neural network (ANN) and improved binary gravitational search algorithm (IBGSA) are utilized to detect objects in images. Watershed algorithm is used to segment images and extract the objects. Color, texture and geometric features are extracted from each object. IBGSA is used as a feature selection method to find the best subset of features for classifying the desired objects...
This paper presents a new algorithm for colorizing gray scale natural still images. The algorithm uses artificial neural network (ANN) to predict the low frequency discrete cosine transform (DCT) components of the RGB channels. A set of natural color images are used to train three ANNs. The trained networks estimates the RGB layers of the gray scale image that best match a set of training colored...
One of the challenges in precision agriculture is the detection of diseased crops in agricultural environments. This paper presents a methodology to detect the Ceratocystis wilt disease in Eucalyptus crops. An unmanned aerial vehicle is used to obtain high-resolution RGB images of a predefined area. The methodology enables the extraction of visual features from image regions and uses several supervised...
Machine vision is still a challenging topic and attracts researchers to carry out researches in this field. Efforts have been placed to design machine vision systems (MVS) that are inspired by human vision system (HVS). Attention is one of the important properties of HVS, with which the human can focus only on part of the scene at a time; regions with more abrupt features attract human attention more...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
Skin detection serves as a preliminary step for number of applications like face detection, gesture recognition, internet pornographic image filtering, and surveillance system. Number of artificial neural network (ANN) based skin detection algorithms have been presented in literature which are mostly based on back propagation (BP) ANNs. This paper attempts to analyze the performance of skin classifiers...
This paper presents a program which identifies the 4-panel LCC equivalent of rice plants using image processing techniques and pattern recognition of the Backpropagation neural network. Images of the fully expanded healthy leaves were captured by digital camera and processed through RGB acquisition, color transformation, image enhancement, image segmentation and feature extraction procedures. The...
Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper,...
With the rise in traffic related crimes the need for an efficient automated surveillance system has become of utmost importance. This paper proposes a system to monitor video from traffic cameras and process it in real time for storing essential information of the vehicles in traffic. Histogram of Oriented Gradients (HOG) of extracted frames is used as features for classification (vehicle frame and...
In automation and standardization of quality of cane sugar in sugar factory, quantized identification process needs to be done. Identification of cane sugar was done based on image of cane sugar. In classification and identification based on image, colour models used could influence success rate of identification. This paper presents comparative study among RGB, HSV, HSI, YCbCr, and L∗a∗b colour models...
The general aim of this research is helping women to perform breast self-examination (BSE) for finding out any abnormality, change, or lump in the breasts. BSE involves checking the breasts for finding abnormalities, lumps, or changes. This paper reports about our initial efforts to detect and track the left and right breasts in real-time imaging. Image frames were processed considering the color...
Tracking objects underwater is a very hard task because of the hostile environment that the water presents. Many parameters should be considered in order to lessen the effect of the hostility. Such parameters underwater are not considered in the vision tracking and/or positioning of objects underwater as long as the image taken is not that distorted. This study proposes an image-based positioning...
This paper discusses the effort of discriminating plaque psoriasis skin lesions using Artificial Neural Network (ANN) for dermatological early diagnosis based on color representations. For any digital acquired images, colors can be identified numerically, for example, with respect to the unique RGB, HSV and YCbCr pixel indices. Previous work have produced intelligent identification models for selected...
The development of autonomous vehicles is a highly relevant research topic in mobile robotics. Road recognition using visual information is an important capability for autonomous navigation in urban environments. Over the last three decades, a large number of visual road recognition approaches have been appeared in the literature. This paper proposes a novel visual road detection system based on multiple...
Object detection problems-skin detection here can be considered as object recognition problems with two classes. In this paper, each given class is clustered using the Kmeans algorithm into multiple subclasses and a Multilayer perceptron (MLP) neural network (NN) is trained for each clusters separately. In the testing phase, each point is compared with centers of clusters and the network related to...
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