scholarly journals Color Classification and Object Recognition for Robot Soccer Under Variable Illumination

10.5772/5125 ◽  
2007 ◽  
Author(s):  
Nathan Lovell ◽  
Vladimir Estivill-Castro
Keyword(s):  
Object Recognition ◽  
Color Classification ◽  
Robot Soccer ◽  
Variable Illumination

Research of Object Recognition Algorithm Based on Variable Illumination

2011 ◽  
Vol 255-260 ◽  
pp. 2096-2100
Author(s):  
Song Hao Piao ◽  
Qiu Bo Zhong ◽  
Shu Ai Wang ◽  
Xian Feng Wang
Keyword(s):  
Image Segmentation ◽  
Object Recognition ◽  
Edge Detection ◽  
Color Image ◽  
Vision System ◽  
Recognition Algorithm ◽  
Color Image Segmentation ◽  
Color Information ◽  
Shape Information ◽  
Variable Illumination

The robot vision system is the critical component of the soccer robot, in football competition, robot perceive the most of the information from the vision system. Because of the variable illumination conditions, the traditional image segmentation method based on color information is not satisfactory. Based on the color information and shape information of the object, this paper proposes a object recognition algorithm that combine color image segmentation with edge detection. This algorithm implement image segmentation use color information in the HSV color space obtain the pixel of the object, then use this pixel implement edge detection to recognize the object. Experiments show that this algorithm can recognize the object exactly in the different illumination conditions, satisfy the requirement of the competition.

scholarly journals Emergent Color Categorization in a Neural Network trained for Object Recognition

2021 ◽  
Author(s):  
Jelmer P de Vries ◽  
Arash Akbarinia ◽  
Alban Flachot ◽  
Karl R Gegenfurtner
Keyword(s):  
Neural Network ◽  
Object Recognition ◽  
Categorical Perception ◽  
Color Contrast ◽  
Color Classification ◽  
Color Categories ◽  
Visual Skills ◽  
Category Formation ◽  
Color Categorization ◽  
Key Questions

Color is a prime example of categorical perception, yet it is still unclear why and how color categories emerge. The key questions revolve around to what extent perceptual and linguistic processes shape categories. While prelinguistic infants and animals appear to treat color categorically, several recent attempts to model category formation have successfully utilized communicative concepts to predict color categories. Considering this apparent discrepancy, we take a different approach. Rather than modeling categories directly, we focus on the potential emergence of color categories as the result of acquiring basic visual skills. For this, we investigated whether color is represented categorically in a convolutional neural network (CNN) trained to recognize objects in natural images. We systematically trained novel output layers to the CNN for a color classification task, and found that clear borders arise between novel (non-training) colors that are largely invariant to the training colors. We confirmed these border locations by searching for the optimal border placement using an evolutionary algorithm that relies on the principle of categorical perception. Our findings also extend to stimuli with multiple, colored, words of varying color contrast, as well as colored objects with larger colored surfaces. These results provide strong evidence that color categorization can emerge with the development of object recognition.

Illumination Invariant Color Model for Object Recognition in Robot Soccer

2010 ◽  
pp. 680-687 ◽  
Author(s):  
Xin Luan ◽  
Weiwei Qi ◽  
Dalei Song ◽  
Ming Chen ◽  
Tieyi Zhu ◽  
...  
Keyword(s):  
Object Recognition ◽  
Color Model ◽  
Illumination Invariant ◽  
Robot Soccer

Use It and Still Lose It?

GeroPsych ◽  
2010 ◽  
Vol 23 (3) ◽  
pp. 169-175 ◽  
Author(s):  
Adrian Schwaninger ◽  
Diana Hardmeier ◽  
Judith Riegelnig ◽  
Mike Martin
Keyword(s):  
Object Recognition ◽  
Cognitive Development ◽  
Recognition Test ◽  
Cognitive Aging ◽  
Recognition Task ◽  
Airport Security ◽  
Visual Object ◽  
Long Term Effects ◽  
Object Recognition Test ◽  
X Ray

In recent years, research on cognitive aging increasingly has focused on the cognitive development across middle adulthood. However, little is still known about the long-term effects of intensive job-specific training of fluid intellectual abilities. In this study we examined the effects of age- and job-specific practice of cognitive abilities on detection performance in airport security x-ray screening. In Experiment 1 (N = 308; 24–65 years), we examined performance in the X-ray Object Recognition Test (ORT), a speeded visual object recognition task in which participants have to find dangerous items in x-ray images of passenger bags; and in Experiment 2 (N = 155; 20–61 years) in an on-the-job object recognition test frequently used in baggage screening. Results from both experiments show high performance in older adults and significant negative age correlations that cannot be overcome by more years of job-specific experience. We discuss the implications of our findings for theories of lifespan cognitive development and training concepts.

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