#hlac

[authortijah]

🗡𝑵𝒆𝒘 𝑹𝒆𝒍𝒆𝒂𝒔𝒆 𝑨𝒍𝒆𝒓𝒕!🗡 Have you read Here Lives a Corpse by @clmatthewsauthor yet? It's now LIVE! Secrets, bloodlines, the price to pay. Download your copy today or read for FREE with Kindle Unlimited! Amazon: mybook.to/HLaC Goodreads: https://bit.ly/393rLB2 #clmatthews #HLaC #DarkRomance #LGBTQA+ #RomanticSuspense #YoungAdultRomance #AntiHero #Bully #Revenge #SecretSociety #ReverseHarem #Bookstagrammer #GreysPromo @greyspromo #BookstagramBlast https://www.instagram.com/p/CGamUYYgrJX/?igshid=8juqy0p39fzr

[joshyconker909]

Kevin Owens and Chris Jericho are my new favorite tagteam 😈 #TheCanadianDestroyesHaveStruckAgain #HlAC #WWE

[jose-montero-blog]

HLAC APP PAPER

[y-takeda]

HLAC特徴量　画像処理

位置不変性の特徴を抽出するようです．

HLAC特徴のわかりやすい説明

http://rest-term.com/archives/2889/

OpenCVを用いてのコード例

http://nosyan.hatenablog.com/entry/20100612/1276355761

↑様のをそのままお借りして，若干の変更とコメントとmain文を追加したプログラムを紹介しておきます．

//2値化画像を想定されたHLAC特徴量です．

//普通の画像から抽出したい場合は，マスクパターンを設定して各輝度値を次元毎に掛け合わせていく事になるのかな？

//ただ，複数のサイトや論文みても2値化で使われています．計算速度との兼ね合いでしょうか．

※double型の配列で出力しています．

void HLAC_Extract(IplImage* input_image, double arrayHLAC[25])

{

int h = input_image->height - 1;//端の例外処理を無くすため

int w = input_image->width - 1;//同じく

int wideStep = input_image->widthStep;

for(int i = 0; i < 25; ++i)

arrayHLAC[i] = 0.0;

// 特徴抽出

for(int iy = 1; iy < h; iy++){

for(int ix = 1; ix < w; ix++){

uchar p5 = (uchar)input_image->imageData[wideStep*iy + ix];

if(p5 != 0)

{

arrayHLAC[0]++;

uchar p1 = (uchar)input_image->imageData[wideStep*(iy-1) + (ix-1)];

uchar p2 = (uchar)input_image->imageData[wideStep*(iy-1) + ix    ];

uchar p3 = (uchar)input_image->imageData[wideStep*(iy-1) + (ix+1)];

uchar p4 = (uchar)input_image->imageData[wideStep*iy     + (ix-1)];

uchar p6 = (uchar)input_image->imageData[wideStep*iy + (ix+1)];

uchar p7 = (uchar)input_image->imageData[wideStep*(iy+1) + (ix+1)];

uchar p8 = (uchar)input_image->imageData[wideStep*(iy+1) + ix    ];

uchar p9 = (uchar)input_image->imageData[wideStep*(iy+1) + (ix+1)];

if(p1 != 0){ arrayHLAC[1]++;

if(p8 != 0) arrayHLAC[13]++;

if(p3 != 0) arrayHLAC[21]++;

if(p7 != 0) arrayHLAC[22]++;

}

if(p2 != 0){ arrayHLAC[2]++;

if(p8 != 0) arrayHLAC[7]++;

if(p7 != 0) arrayHLAC[11]++;

if(p9 != 0) arrayHLAC[12]++;

if(p6 != 0) arrayHLAC[17]++;

}

if(p3 != 0){ arrayHLAC[3]++;

if(p7 != 0) arrayHLAC[6]++;

if(p4 != 0) arrayHLAC[9]++;

if(p8 != 0) arrayHLAC[14]++;

}

if(p4 != 0){ arrayHLAC[4]++;

if(p6 != 0) arrayHLAC[5]++;

if(p9 != 0) arrayHLAC[10]++;

if(p2 != 0) arrayHLAC[18]++;

if(p8 != 0) arrayHLAC[19]++;

}

if(p6 != 0){

if(p7 != 0) arrayHLAC[15]++;

if(p1 != 0) arrayHLAC[16]++;

if(p8 != 0) arrayHLAC[20]++;

}

if(p9 != 0){

if(p1 != 0) arrayHLAC[8]++;

if(p7 != 0) arrayHLAC[23]++;

if(p3 != 0) arrayHLAC[24]++;

}

}

}

}

}

int main(){

double hlac_feature[25];

IplImage* img=cvLoadImage("../../lena.png",0);

IplImage* bin_img=cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);

cvThreshold(img, bin_img, 0, 255, CV_THRESH_BINARY|CV_THRESH_OTSU);//2値化している．

HLAC_Extract(bin_img,hlac_feature);

for(int i=0;i<25;i++)

std::cout<<"HLAC"<<i<<":"<<hlac_feature[i]<<"\n";

getchar();

}

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