Color Matching Method for Foreground Based on Complex Background Image Processing: Example of Mobile Phone Interface

2021 ◽  
pp. 915-922
Author(s):  
Lanjing Li ◽  
Dongke Sun
Keyword(s):  
Image Processing ◽  
Mobile Phone ◽  
Color Matching ◽  
Matching Method ◽  
Complex Background ◽  
Background Image

Algorithm of Color Detection for Moving Video Objects Based on Mode Matching

2012 ◽  
Vol 239-240 ◽  
pp. 1000-1003
Author(s):  
Zhao Quan Cai ◽  
Hui Hu ◽  
Tao Xu ◽  
Wei Luo ◽  
Yi Cheng He
Keyword(s):  
Background Subtraction ◽  
Moving Objects ◽  
Color Matching ◽  
Human Beings ◽  
Current Image ◽  
Color Recognition ◽  
Recognition Ability ◽  
Color Identification ◽  
The Difference ◽  
Background Image

It is urgent to study how to effectively identify color of moving objects from the video in the information era. In this paper, we present the color identification methods for moving objects on fixed camera. One kind of the methods is background subtraction that recognizes the foreground objects by compare the difference of pixel luminance between the current image and the background image at the same coordinates. Another kind is based on the statistics of HSV color and color matching which makes the detection more similar to the color identification of the human beings. According to the experiment results, after the completion of the background modelling, our algorithm of background subtraction, statistics of the HSV color and the color matching have strong color recognition ability on the moving objects of video.

scholarly journals Template Matching dalam Otomatisasi Penghitung Sel Keping Darah Berbasis Image Processing untuk Deteksi Dini Derajat Penyakit Demam Berdarah

2018 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Amelia Yolanda ◽  
Deddy Prayama ◽  
Aulia Ramadhani
Keyword(s):  
Image Processing ◽  
Dengue Hemorrhagic Fever ◽  
Template Matching ◽  
Hemorrhagic Fever ◽  
Matching Method ◽  
System Testing ◽  
Blood Tests ◽  
Automatic Systems

One of the diseases that can be detected through blood tests is Dengue Hemorrhagic Fever (DHF). The number of platelets are one of the guidelines used by doctors diagnosing DHF. Actually, platelets can be calculated manually, but it will be very difficult if the platelets are counted quite a lot. So, we need a technology that can calculate the number of platelets quickly and automatized to get more accurate results.   The automatic systems built by using the template matching method with  image processing include HSL Segmentation with Luminance type and Reverse Color Manipulation. After building the system, the system will automatically look for objects that match the template in the sample image and then give the marking and calculate it.The overall system testing results are the number of platelets which are then classified manually at what degree of DHF.

Mobile Phone and Visual Tags

2011 ◽  
pp. 1-22
Author(s):  
Marco Avvenuti ◽  
Alessio Vecchio
Keyword(s):  
Image Processing ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Digital Information ◽  
Computing Environment ◽  
Mass Market ◽  
Camera Phones ◽  
Networked Computing ◽  
Real Objects ◽  
Smart Mobile

The growing ubiquity and usability of smart mobile phones can be exploited to develop popular and realistic pervasive computing applications. Adding image processing capabilities to a mobile phone equipped with a built-in camera makes it an easy-to-use device for linking physical objects to a networked computing environment. This chapter describes an extensible and portable programming platform that, using bi-dimensional visual tags, turns mass-market camera-phones into a system able to capture digital information from real objects, use such information to download specific application code, and act as a GUI for interacting with object-dependent computational services. The system includes a module for on-phone extraction of visual coded information and supports the dynamic download of mobile applications.

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