The application of improved HSV color space model in image processing

2010 ◽  
Author(s):  
Li Shuhua ◽  
Guo Gaizhi
Keyword(s):  
Image Processing ◽  
Color Space ◽  
Hsv Color Space ◽  
Space Model

scholarly journals A G-Fresnel Optical Device and Image Processing Based Miniature Spectrometer for Mechanoluminescence Sensor Applications

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3528 ◽  
Author(s):  
Min ◽  
Kim ◽  
Song ◽  
Kim
Keyword(s):  
Image Processing ◽  
Visible Light ◽  
Color Space ◽  
Image Sensor ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Spectral Image ◽  
Optical Device ◽  
Hsv Color Space ◽  
Color Space Conversion

This paper presents a miniature spectrometer fabricated based on a G-Fresnel optical device (i.e., diffraction grating and Fresnel lens) and operated by an image-processing algorithm, with an emphasis on the color space conversion in the range of visible light. The miniature spectrometer will be cost-effective and consists of a compact G-Fresnel optical device, which diffuses mixed visible light into the spectral image and a μ-processor platform embedded with an image-processing algorithm. The RGB color space commonly used in the image signal from a complementary metal–oxide–semiconductor (CMOS)-type image sensor is converted into the HSV color space, which is one of the most common methods to express color as a numeric value using hue (H), saturation (S), and value (V) via the color space conversion algorithm. Because the HSV color space has the advantages of expressing not only the three primary colors of light as the H but also its intensity as the V, it was possible to obtain both the wavelength and intensity information of the visible light from its spectral image. This miniature spectrometer yielded nonlinear sensitivity of hue in terms of wavelength. In this study, we introduce the potential of the G-Fresnel optical device, which is a miniature spectrometer, and demonstrated by measurement of the mechanoluminescence (ML) spectrum as a proof of concept.

scholarly journals Deteksi Kelayuan Pada Bunga Mawar dengan Metode Transformasi Ruang Warna Hue Saturation Intensity (HSI) dan Hue Saturation Value (HSV)

2021 ◽  
Vol 5 (1) ◽  
pp. 308
Author(s):  
Dede Wandi ◽  
Fauziah Fauziah ◽  
Nur Hayati
Keyword(s):  
Image Processing ◽  
System Design ◽  
Research Methods ◽  
Color Space ◽  
Literature Study ◽  
Hsv Color Space ◽  
Saturation Intensity ◽  
The Rose

The rose is a plant of the genus Rosa. The rose consists of more than 100 species with various colors. In selecting and sorting roses, roses are often found that are still fresh and wilted. Based on the problems faced in roses, a system design is carried out that can detect the wilting condition of roses. By applying the HSI and HSV methods to image processing applications, it is hoped that it can help in choosing the condition of roses. With research methods through observation and literature study. To see the conditions, roses can be divided into wilted flowers and fresh flowers. In its implementation and classification, by detecting the color of roses in the HSI and HSV color space, from a total of 230 images of red and white roses that tested 200 images using HSI and HSV, the value of Range was obtained on the HSI, H = 0.240634 - 0.5, S = 0.781818 - 1, and I = 0.477124 - 1 in the Fresh category, while the HSI Wilt Category, H = 0.170495 - 0.5, S = 0.40239 - 1, I = 0.562092 - 1. and also obtained the value of Range with HSV with Fresh category H = 0.240634 - 0.5, S = 0 - 0.988235, V = 0 - 0.988235, and Wilt category H = 0.170495-0.5, S = 0 - 0.996078, V = 0 - 0.996078. With an accuracy value of the HSI and HSV of 86.9%. Therefore, it can be concluded that the detection of wilting in roses using the HSI and HSV methods is the fastest in the process using the HSI method because it reads all the min-max values.

scholarly journals Interactive Color Image Segmentation using HSV Color Space

2019 ◽  
Vol 7 (1) ◽  
pp. 37-41
Author(s):  
D. Hema ◽  
◽  
Dr. S. Kannan ◽  
Keyword(s):  
Image Segmentation ◽  
Object Detection ◽  
Color Image ◽  
Research Work ◽  
Color Space ◽  
Color Image Segmentation ◽  
Hsv Color Space ◽  
Space Model ◽  
Detection Algorithms ◽  
Rgb Image

The primary goal of this research work is to extract only the essential foreground fragments of a color image through segmentation. This technique serves as the foundation for implementing object detection algorithms. The color image can be segmented better in HSV color space model than other color models. An interactive GUI tool is developed in Python and implemented to extract only the foreground from an image by adjusting the values for H (Hue), S (Saturation) and V (Value). The input is an RGB image and the output will be a segmented color image.

scholarly journals Load Position Detection of Container Crane Using Camera

2021 ◽  
Vol 31.2 (149) ◽  
pp. 65-71
Keyword(s):  
Image Processing ◽  
Color Space ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Camera System ◽  
Hsv Color Space ◽  
Container Cranes ◽  
Container Crane ◽  
Position Detection ◽  
Main Input

In this study, the authors proposed an image processing algorithm to detect (measure) the rope length of container crane (distance from camera system to container spreader) and sway angle of the spearder (container). This measurement will be the main input to design the anti-sway control system for container cranes. The image processing algorithm includes the main steps: converting from BGR color space to HSV color space, then, binary image is used to extract the marker area. Next, the Canny boundary detection technique is applied to determine the boundary of the markers in the container spreader. The center location of each marker is determined and used to calculate the distance from the camera system to the container spreader is calculated. The rope length accuracy by the image processing algorithm is 99,79%. It is satisfied for crane control purpose.

Color and Texture Features Based Image Retrieval

2013 ◽  
Vol 441 ◽  
pp. 707-710
Author(s):  
Ching I Lin ◽  
Ching Hung Su ◽  
Shih Hung Tai
Keyword(s):  
Image Retrieval ◽  
Color Space ◽  
Texture Features ◽  
Color Code ◽  
Hsv Color Space ◽  
Space Model ◽  
Retrieval Scheme ◽  
Color Pixel ◽  
Color And Texture Features

We propose a practical image retrieval scheme to retrieve images efficiently. We propose a scheme using color and texture features and address the unique algorithm to extract the color pixel features by the HSV color space and Tamura features of the texture features. The proposed scheme transfers each image to a quantized color code using the regulations of the properties in compliance with HSV color space model and then employing the quantized color code along with Tamura features of texture features to compare the images of database. Experimental of the proposed scheme on demonstrate more efficient and effective than the conventional schemes.

scholarly journals THE DEVELOPMENT OF IMAGE PROCESSING METHOD ON THE AUTOMATIC READING SYSTEM OF THE GLASS THERMOMETER USING A DIGITAL CAMERA

2021 ◽  
Vol 6 (1) ◽  
pp. 1-8
Author(s):  
Gianto Gianto ◽  
Vera Firmansyah ◽  
Irwan Setiawan ◽  
Achsan Rifani
Keyword(s):  
Image Processing ◽  
Human Error ◽  
Color Space ◽  
Digital Camera ◽  
Processing Method ◽  
Synthetic Image ◽  
Hsv Color Space ◽  
Image Processing Method ◽  
Unit Value ◽  
Reading System

The reading performance of an analog thermometer, Liquid in Glass Thermometer (LiGT), can be improved using a digital camera. The aim is to minimize the human error on the reading of LiGT and increase the accuracy of temperature measurement results. In order to achieve an accurate result, a robust image processing method is required in the measurement. In this work, the LiGT image generated using a digital camera is analyzed using the technique in HSV color space which consists of some image processing methods (e.g., thresholding, morphology filter). The type of LiGT used is the glass thermometer with the colored liquid. There are three main parts to this developed technique process, i.e., identifying the scale of LiGT to calculate the pixel per temperature unit value (ppt), segmentation of the liquid column, and calculate the temperature based on the ppt value. Through simulation with a synthetic image, we demonstrate that the developed technique in this work has successfully read (measured) the temperature value of the LiGT (having a scale unit of 1oC) with a measurement error of 0.04oC. In the experimental results, we also report the developed technique performed on a real image of LiGT.

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

scholarly journals Automated Segmentation of Leukocytes using Marker-based Watershed Algorithm from Blood Smear Images

2021 ◽  
Author(s):  
Vipasha Abrol ◽  
Sabrina Dhalla ◽  
Jasleen Saini ◽  
Ajay Mittal ◽  
Sukhwinder Singh ◽  
...  
Keyword(s):  
Image Processing ◽  
Blood Smear ◽  
White Blood Cells ◽  
Color Space ◽  
Specific Marker ◽  
Watershed Algorithm ◽  
Hsv Color Space ◽  
Whole Process ◽  
Proposed Model ◽  
Processing Techniques

The aim of this paper is to perform segmentation of white blood cells (WBCs) using blood smear images with the help of image processing techniques. Traditionally, the process of morphological analysis of cells is performed by a medical expert. This process is quite tedious and time consuming. The equipments used to perform the experiments are very costly and might not be available in all hospitals. Further, the whole process is quite lengthy and prone to error easily because of the lack of standard set of procedure. Hence there is a need for innovative and efficient techniques. An automated image segmentation system can make the blood test process much easier and faster. Segmentation of a nucleus image is one of the most critical tasks in a leukemia diagnosis. In this work, we have investigated and implemented image processing algorithms to segment cells. The proposed model detects WBCs and converts cell images from RGB to HSV color space using Otsu thresholding. The resultant image is then processed with the morphological filter because the segmented image contains noise which affects the system performance. Lastly, the Marker-based watershed algorithm is implemented in which specific marker positions are defined. The proposed model is tested on publically available ALL-IDB2 dataset. The system’s performance was overall examined and resulted in 98.99% overall precision for WBC segmentation.

scholarly journals Enhancing the Tablet Images using Noise Reduction Algorithms by Analyzing Different Color Models

2019 ◽  
Vol 9 (2) ◽  
pp. 148-155
Keyword(s):  
Healthcare Professionals ◽  
Wavelet Packet ◽  
Color Space ◽  
Packet Transmission ◽  
Maximum Efficiency ◽  
Identification System ◽  
Discrete Wavelet ◽  
Hsv Color Space ◽  
Space Model ◽  
Different Color

Unidentified tablets are challenges to both patients and healthcare professionals. Using these unknown tablets results in undesirable reaction of drug and also it is foundation to ill health that leads to death even sometimes. Thus, recognition of unidentified tablets is a significant task in medical industry. Identification of tablets is one of the major concerns for public and pharmacists, which can be carried out by means of either text-based or image-based methods. The tablet identification system is focused on removing noise from the tablet images using algorithms like Independent Component Analysis (ICA) and Discrete Wavelet Packet Transmission (DWPT). The three color space models, i.e., RGB (Red-Green-Blue), YCbCr (Y-Luma, CChroma of blue and red components) and HSV (Hue-SaturationValue) are examined for their efficiency on removing noise from tablets. For each color space model, the two denoising algorithms, ICA and DWPT are analyzed and applied. The result is interpreted using metrics like PSNR, FoM, MSSI and Speed. Experimental results proved that denoising with HSV color space model gives maximum efficiency when used with ICA and DWPT-based tablet identification systems.

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