scholarly journals Construction of object boundaries for the autopilot of a surface robot from satellite images using computer vision methods

2021 ◽  
pp. 107-118
Author(s):  
A.N. Grekov ◽  
◽  
Y.E. Shishkin ◽  
S.S. Peliushenko ◽  
A.S. Mavrin ◽  
...  
Keyword(s):  
Computer Vision ◽  
Digital Image ◽  
Satellite Images ◽  
Color Space ◽  
Image Filtering ◽  
Water Bodies ◽  
Hsv Color Space ◽  
The One

An algorithm and a program for detecting the boundaries of water bodies for the autopilot module of a surface robot are proposed. A method for detecting water objects on satellite maps by the method of finding a color in the HSV color space, using erosion, dilation - methods of digital image filtering is applied. The following operators for constructing contours on the image are investigated: the operators of Sobel, Roberts, Prewitt, and from them the one that detects the boundary more accurately is selected for this module. An algorithm for calculating the GPS coordinates of the contours is created. The proposed algorithm allows saving the result in a format suitable for the surface robot autopilot module.

3D Object’s Pose Estimation Based on Colored Markers Information

2013 ◽  
Vol 846-847 ◽  
pp. 1162-1165
Author(s):  
Xiang Gao ◽  
Chong Zhang ◽  
Chun Gang Zhang ◽  
Xi Juan Guo
Keyword(s):  
Computer Vision ◽  
Pose Estimation ◽  
Color Space ◽  
Estimation Method ◽  
Regions Of Interest ◽  
Experimental Results ◽  
Feature Points ◽  
Hsv Color Space ◽  
Rigid Objects ◽  
The Stability

Pose estimation of 3d object is a hot research in the field of computer vision. This paper presents a novel pose estimation method based on colored markers. To overcome the effect of the luminance and other colors, this method uses the HSV color space and isolates the colors operating only on chromaticity plane where value (V) has no actual effect for identifying the colored regions of interest. The template is then applied on the remaining colors in order to find the center of the region. The pixels which have the same color but are not in the marker area are excluded, since they are considered noisy. The template guarantees the stability and efficiency of the extraction of the feature points. Compared with the CDT algorithm, the proposed method can extract reliable center points, and has higher accuracy in pose estimation for planar rigid objects. At last, experimental results demonstrate the efficiency of the method.

Analysis on the Static Features of Flame Images

2013 ◽  
Vol 765-767 ◽  
pp. 2403-2406
Author(s):  
Jing Du ◽  
Yun Yang Yan ◽  
Xi Yin Wu ◽  
Yian Liu
Keyword(s):  
Computer Vision ◽  
Feature Extraction ◽  
Local Binary Pattern ◽  
Color Space ◽  
Fire Detection ◽  
Visual Saliency ◽  
Fire Prevention ◽  
Hsv Color Space ◽  
Saliency Model ◽  
Rgb Color Space

Fire detection based on images is an effective method for fire prevention, especially in big room or badly environment. It is important to extract the features of a flame image. According to the idea of visual saliency in computer vision, saliency model of brightness, color and flame texture are proposed here. The saliency of flame brightness is indicated by the V component in HSV color space. The saliency of flame color is expressed by the relation of R and B in the RGB color space. The saliency of flame texture is described by the distance between the feature vectors which are the combination of features with Local Binary Pattern. Experimental results show the saliency model is effective for flame feature extraction.

scholarly journals Robust Reflection Detection and Removal in Rainy Conditions using LAB and HSV Color Spaces

2016 ◽  
Author(s):  
Synh Viet-Uyen Ha ◽  
Nhan Thanh Pham ◽  
Long Hoang Pham ◽  
Ha Manh Tran
Keyword(s):  
Computer Vision ◽  
Color Space ◽  
Traffic Monitoring ◽  
Monitoring Systems ◽  
Color Spaces ◽  
Hsv Color Space ◽  
Removal Method ◽  
Causes Of Errors ◽  
Lab Color Space ◽  
Optimal Intensity

In the field of traffic monitoring systems, shadows are the main causes of errors in computer vision-based vehicle detection and classification. A great number of  research have been carried out to detect and remove shadows. However, these research works only focused on solving shadow problems in daytime traffic scenes. Up to now, far too little attention has been paid to the problem caused by vehicles’ reflections in rainy conditions. Unlike shadows in the daytime, which are homogeneous gray shades, reflection shadows are inhomogeneous regions of different colors. This characteristic makes reflections harder to detect and remove. Therefore, in this paper, we aim to develop a reflection detection and removal method from single images or video. Reflections are detected by determining a combination of L and B channels from LAB color space and H channel from HSV color space. The reflection removal method is performed by determining the optimal intensity of reflected areas so that they match with neighbor regions. The advantage of our method is that all reflected areas are removed without affecting vehicles’ textures or details.

scholarly journals Implementasi Pengolahan Citra Digital Sebagai Pengukur Nilai Resistor Pada Sistem Pemindai Resistor Berbasis Android

2015 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Satrio Firmansyah ◽  
Danang Lelono ◽  
Rade Sumiharto
Keyword(s):  
Image Processing ◽  
Light Intensity ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Space ◽  
Detection Distance ◽  
Hsv Color Space ◽  
Maximum Value ◽  
Actual Color ◽  
Color Value

AbstrakSalah satu gadget yang sering digunakan adalah telepon pintar berbasis Android. Android bersifat Open Source sehingga memungkinkan pengguna dan pengembang dalam mengoperasikan maupun membuat aplikasi berbasis Android. Ada berbagai macam permasalahan yang membutuhkan citra sebagai masukan atau input sistem dikarenakan keterbatasan manusia dalam hal kecepatan memproses suatu fungsi matematis maupun algoritma pendukung didalamnya, selain itu juga masalah waktu dan lain sebagainya. Salah satu sistem yang membutuhkan citra sebagai masukannya adalah penentuan nilai resistor berdasarkan gelang warna. Untuk melakukan seleksi warna digunakan metode segmentasi warna pemodelan warna HSV. Dengan menggunakan model warna HSV dapat menjadi model warna yg dapat digunakan sebuah sistem untuk menentukan nilai warna resistor, karena komponen nilai hue adalah representasi dari nilai warna yang sebenarnya. Hal ini didukung dengan saturation yang berfungsi sebagai tingkat kejenuhan suatu warna dan nilai value sebagai nilai kecerahan warna. Uji coba sistem dilakukan dengan pengujian pengaruh intensitas cahaya dan jarak pendeteksian antara kamera dan resistor.Hasil dari penelitian ini berupa sebuah implementasi pengolahan citra digital sebagai pengukur nilai resistor. Hasil terbaik dicapai dengan kondisi ruangan pada intensitas cahaya lampu antara 400 lux hingga 1200 lux dengan jarak pendeteksian antar kamera dan resistor yaitu maksimal 20 cm. Kata kunci— pengolahan citra digital, Android, resistor, HSV, intensitas cahaya, java AbstractOne of the gadget that is often used is Android smart phones. Android is an OpenSource, it could help user and developer to operate and develop Android Application. There are several problems that need image as an input system, it is caused by the humas’s ability in doing some mathematic functions or supported algorythm. To make the selection color used HSV color space. By using HSV color space allows a system to determine the color value resistor, because the hue value of the component is a representation of the actual color value. This is supported by the saturation level that serves as a color saturation and value as a brightness of color.The results of this research is an implementation of digital image processing as a measure of the value of the resistor. The system is tested by the influence of light intensity and the distance between the camera and resistor. The best results were achieved with the conditions of the room in light intensity between 400 lux to 1200 lux the detection distance between the camera and resistor is 20 cm of maximum value. Keywords—digital image processing, Android, resitor, HSV, light intensity, java

HSV Based Image Forgery Detection for Copy-Move Attack

2014 ◽  
Vol 556-562 ◽  
pp. 2825-2828
Author(s):  
Bo Liu ◽  
Chi Man Pun
Keyword(s):  
Digital Image ◽  
Color Space ◽  
Experimental Result ◽  
Forgery Detection ◽  
Image Forgery ◽  
Hsv Color Space ◽  
News Photography ◽  
Image Forgery Detection ◽  
Novel Method ◽  
Digital Image Forgery

As the great development of digital photography and relevant post-processing technology, digital image forgery becomes easily in terms of operating thus may be improperly utilized in news photography in which any forgery is strictly prohibited or the other scenario, for instance, as an evidence in the court. Therefore, digital image forgery detection technique is needed. In this paper, attention has been focused on copy-move forgery that one region is copied and then pasted onto other zones to create duplication or cover something in an image. A novel method based on HSV color space feature is proposed and experimental result will be given and it shows the effectiveness and accurateness of proposed methodology.

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

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