一種新型增加去霧處理的車牌檢測(cè)算法在林區(qū)中的應(yīng)用

1、    一種新型增加去霧處理的車牌檢測(cè)算法在林區(qū)中的應(yīng)用    丁鍵 朱洪前 任會(huì) 李丹 楊國(guó)摘 要：林區(qū)的治安防護(hù)管理一直是人們所欠缺關(guān)注的問(wèn)題，林區(qū)作案、林區(qū)動(dòng)植物的盜伐都透露出林區(qū)治安防護(hù)管理的短板。本文致力于機(jī)器視覺(jué)在林區(qū)的應(yīng)用，為加強(qiáng)林區(qū)的防盜伐能力提出一種融合圖像去霧處理的車牌檢測(cè)算法，該方法采用限定對(duì)比度自適應(yīng)直方圖均衡化的技術(shù)去除大霧天、雨雪天等圖像模糊的干擾，結(jié)合車牌的顏色、長(zhǎng)寬比形態(tài)等特征對(duì)霧雨雪天氣下的車牌進(jìn)行檢測(cè)。該方法相比普通車牌檢測(cè)方法的效果有較大提升，霧雨雪天氣環(huán)境下檢測(cè)車牌的準(zhǔn)確率可以達(dá)到88.00%，而普通車牌檢測(cè)方法達(dá)

2、到的準(zhǔn)確率僅為82.67%。初步證明了本文提出的算法在林區(qū)霧雨雪天氣下應(yīng)用的可行性。關(guān)鍵詞：林區(qū)防護(hù);限定對(duì)比度自適應(yīng)直方圖均衡化;車牌檢測(cè);去霧處理;復(fù)雜天氣環(huán)境中圖分類號(hào)：tp391.4;u495    文獻(xiàn)標(biāo)識(shí)碼：a   文章編號(hào)：1006-8023（2021）04-0094-08application of a novel algorithm for license plate detection withdefogging processing in forest regionding jian， zhu hongqian*， ren

3、 hui， li dan， yang guo（college of materials science and engineering， central south university of forestry and technology， changsha 410004， china）abstract：the management of public security protection in forest areas has always been a problem that people lack attention to. it reveals the weakness of p

4、ublic security protection management in forest areas that committing crimes， illegal felling of trees and poaching animals. our group has been committed to the application of machine vision in forest areas. in order to enhance the ability of forest area to prevent illegal cutting， this paper present

5、s a novel algorithm of license plate detection which combines image defogging processing. this method uses the technique of contrast limited adaptive histogram equalization to remove the interference of image blurring in foggy， rainy and snowy days， and combines the features of the license plate suc

6、h as color， aspect ratio， etc. to detect the license plate in fog， rain and snow weather. compared with the ordinary license plate detection method， the result of this method has been greatly improved. the accuracy of detecting license plate in fog， rain and snow weather can reach 88.00%， while the accuracy of ordinary license plate detection can only reach 82.67%. this paper preliminarily proves the feasibility of the proposed algorithm in fog， rain and snow weather of forest areas.keywords：forest protection; contrast limited adaptive his