CIRCULAR TRAFFIC SIGN CLASSIFICATION USING HOGBASED RING PARTITIONED MATCHING
نویسندگان
چکیده
منابع مشابه
Circular Traffic Sign Classification Using Hog- Based Ring Partitioned Matching
This paper presents a technique to classify the circular traffic sign based-on HOG (histogram of oriented gradients) and a ring partitioned matching. The method divides an image into several ring areas, and calculates the HOG feature on each ring area. In the matching process, the weight is assigned to each ring for calculating the distance of HOG feature between tested image and reference imag...
متن کاملTraffic Sign Classification Using Ring Partitioned Method
--Traffic sign recognition usually consists of two parts : detection and classification. In this paper we describe the classification stage using ring partitioned method. In this method, first the RGB image is converted into gray scale image using color thresholding and histogram specification technique. This gray scale image, called as specified gray scale image is invariant to the illuminatio...
متن کاملTraffic sign classification using error correcting techniques
Traffic sign classification is a challenging problem in Computer Vision due to the high variability of sign appearance in uncontrolled environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a classification technique for traffic signs recognition by means of Error Correcting Output Codes. Recently, new proposals of cod...
متن کاملTechniques for Traffic Sign Classification Using Machine Learning-a Survey
The Road Sign Recognition is a field of applied computer vision research concerned with the automatic detection and classification of traffic signs in traffic scene images. The aim of this research paper is to study the various classification techniques that can be used to construct a system that recognizes road signs in images. The primary objective is to develop an algorithm which will identi...
متن کاملTraffic Sign Classification Using Deep Inception Based Convolutional Networks
In this work, we propose a novel deep networks for traffic sign classification that achieves outstanding performance on GTSRB surpassing all previous methods. Our deep network consists of spatial transformer layers and a modified version of inception module specifically designed for capturing local and global features together. This features adoption allows our network to classify precisely int...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal on Smart Sensing and Intelligent Systems
سال: 2017
ISSN: 1178-5608
DOI: 10.21307/ijssis-2017-232