FPGA二值图像边界提取算法实现.doc
FPGA二值图像边界提取算法实现1 背景知识如图1 所示，图1 a为一幅简单的二值图像，经过边界提取后形成如图1 b 所示的图像，显示出了白色区域的轮廓。2 边界提取算法使用黑色提取，背景为白色，1表示白色，0表示黑色。我们使用3x3模板进行边界提取，所以当3x3九个点都是1的时候，输出为1，当九个点都是0的时候，输出为1，其他情况输出均为0。3 FPGA二值图像边界提取算法实现图2中我们使用串口传图传入的是二值图像。FPGA源码：/*Module name: boundary_extracTIon.vDescripTIon: binary image boundary extracTIon*/TImescale 1ns/1psmodule boundary_extraction( input clk, /pixel clkinput rst_n,input hs_in,input vs_in,input 15:0 data_in,input data_in_en,output hs_out,output vs_out,output reg 15:0 data_out,output data_out_en);wire 15:0 line0;wire 15:0 line1;wire 15:0 line2;reg 15:0 line0_data0;reg 15:0 line0_data1;reg 15:0 line0_data2;reg 15:0 line1_data0;reg 15:0 line1_data1;reg 15:0 line1_data2;reg 15:0 line2_data0;reg 15:0 line2_data1;reg 15:0 line2_data2;reg data_out_en0;reg data_out_en1;reg data_out_en2;reg hs_r0;reg hs_r1;reg hs_r2;reg vs_r0;reg vs_r1;reg vs_r2;wire18:0 result_data;line3x3 line3x3_inst( .clken(data_in_en), .clock(clk), .shiftin(data_in), .shiftout(), .taps0x(line0), .taps1x(line1), .taps2x(line2) );/-/ Form an image matrix of three multiplied by three/-always (posedge clk or negedge rst_n) begin if(!rst_n) begin line0_data0 = 16b0;line0_data1 = 16b0;line0_data2 = 16b0;line1_data0 = 16b0;line1_data1 = 16b0;line1_data2 = 16b0;line2_data0 = 16b0;line2_data1 = 16b0;line2_data2 = 16b0;data_out_en0 = 1b0;data_out_en1 = 1b0;data_out_en2 = 1b0;hs_r0 = 1b0;hs_r1 = 1b0;hs_r2 = 1b0;vs_r0 = 1b0;vs_r1 = 1b0;vs_r2 = 1b0; end else if(data_in_en) begin line0_data0 = line0;line0_data1 = line0_data0;line0_data2 = line0_data1;line1_data0 = line1;line1_data1 = line1_data0;line1_data2 = line1_data1;line2_data0 = line2;line2_data1 = line2_data0;line2_data2 = line2_data1;data_out_en0 = data_in_en;data_out_en1 = data_out_en0;data_out_en2 = data_out_en1; hs_r0 = hs_in;hs_r1 = hs_r0;hs_r2 = hs_r1;vs_r0 = vs_in;vs_r1 = vs_r0;vs_r2 = vs_r1; endend/-/ line0_data0 line0_data1 line0_data2/ line1_data0 line1_data1 line1_data2/ line2_data0 line2_data1 line2_data2/-always (posedge clk or negedge rst_n) begin if(!rst_n) data_out = 16h0000; else if(data_out_en1) if(line0_data0 = 16h0000) (line0_data1 = 16h0000) (line0_data2 = 16h0000) (line1_data0 = 16h0000) (line1_data1 = 16h0000) (line1_data2 = 16h0000) (line2_data0 = 16h0000) (line2_data1 = 16h0000) (line2_data2 = 16h0000) data_out = 16hffff; else if(line0_data0 = 16hffff) (line0_data1 = 16hffff) (line0_data2 = 16hffff) (line1_data0 = 16hffff) (line1_data1 = 16hffff) (line1_data2 = 16hffff) (line2_data0 = 16hffff) (line2_data1 = 16hffff) (line2_data2 = 16hffff) data_out = 16hffff; else data_out = 16h0000;endendmodule4实验结果结果分析：图5和图7对比，比较粗的线都被查找出了边缘，只有最细的那条没有被提取出来，并且被加粗，原因是最细的线条只有三个像素当查找出边缘后显示为黑色，两边黑色连在一起所以线条就变粗了。图6和图8边缘查找没有问题。
