参考:
C# 条码标签打印程序,RDLC报表动态显示多条码标签的方法
http://www.cnblogs.com/vice/p/4105898.html
我做的思路是:不使用数据库存储image的byte[]数据,而是首先将所有需要的条码数据保存到一个数据库表中,然后在需要将条码显示到RDLC报表中时,取得表中的条码数据,然后创建数据集(用于存储报表中需要用到的所有数据),再将每条条码数据用barcodelib.dll生成条码对象,返回image对象,再使用下面方法将返回的image对象转换为byte[]数组存入新建的数据集中。
其他代码就不贴了,因为好多东西都没封装都是码上去的,太长了。

1 //image对象转byte数组
2 public static byte[] ImageToBytes(Image img)
3 {
4 ImageConverter imgconv = new ImageConverter();
5 byte[] b = (byte[])imgconv.ConvertTo(img, typeof(byte[]));
6 return b;
7 }

然后在RDLC中创建模板,添加数据源为刚刚创建的数据集,插入图片对象,图像源选择数据库,”使用此字段“ 输入 System.Convert.ToBase64String(Fields!存储image对象的byte[]列名.Value)
方法二:直接在后台字段中先转换为Base64字符串
System.Convert.ToBase64String(ImageToBytes(image));
barcodelib.dll的调用方法封装
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ZP46U2j3StfbQ40r12aLytDo901TGuj3TJVT/HI13yNmt+3m6o5tDv0k1b687SARzlRmeiVjiLr2TxhEc+8OUX7z7dNdJt2KXMVpqlkHh3DIWSTB7NjChI7bPCag7bI9K1IuZWkS5zfM6XzeW5srD8pbplzb6a2uN36aaPh7rUXQXAhm50unlMfmaFrWqZl4Kn1XW12ux2IK6561Z6vZSvGQ9zuolmT5NryZRPVzfrf1mt9TjY8uXWq34SovWhh6C8WrO79tkwu6Nrbb34+KwfDCORbui32ZLNVsu7NZNBrTpRl1lR/BLAtpxuyKrGiI83S3KH9+ckvmyWdcGr9epoC/H8X1ktM0FY3nht9cGv0wGHc7qhozVPcx+2AADn5yoFAHB5Ih0AwOWJdAAAlyfSAQcY+tzA6HcIZ75z7vAtALAt5zVgS/mvo4uDV/xSUDn+apLk2gEu5y4nsvwnFh/Fz7Z96LZ5+Ocr9xj7OTuzeZvVr5ELqu2xlWbfurJ40y1bMJnnZoWZ73Xr1p81O/QdKCId8AFudCLLX59mF8XN155p86g4tX7sm/f81eAZImZg9K94bRjpnuGOW7zddop00/LuDFk+0s0qV2fg5Dngg93oXLYs0r151fv14W3r3XXrnTbVLchnnxfpRv+GROtpddnRb/ptVfadwMCnutFZLH8LrzUt1LqxNX1QrRmssdWlakly7cHAh4ZfrrccV/XVci3BgkP9mbWQ2fKvauVSyY2Z6WqQz1q3Wasl1T8INn0wtJXyx1J1mK1tVW3zOfJbdNVXy1w1DVtxAptN5pX/ttYYdx7gQm50FguueWXN6iW/9Ti42k3zxFCXum221r7VtuqOPbNxuovH22f9lo9XVM00rWHGnWzlreBubPC0muoyu6x6POS30rKx/1hn0T3N+LfoqpmsumD1gxEiHXArNzqLDUW6eJFugpldX3eNdJmBl11atsWCDDS0QWYNLo508Xi7KxrKOgdGumU7K95Q1a1UbTN5wIzedU1+6DXZ8tAsnRuvwEe60VlsQaTLLJ7MNKNd2jDSbbjFulsmP/ydIl0rii2OdM9Gcp25VqRLBtah/wNsPkv3erWavTaZpQP4JDc6u7XmYIYiSPw4XlGysPt010i3YZcyY58lrXh3DGXHTB7NjCjIOrPCag7bI9J1D9oFOy6/B6tG81z5OdZ4Pq/bePUW6uJeAVzRjU5hj8nPrLBaLWghbrPVSLLw8fVnwdo330qvl/I142G+Hr/+nT3Ib+GgfLq6Wf/Laq3HwZYvt171kxCtDz0E5dWamc1b7WeyPHhaXeOXpyPhaehzrMnGWxmx1Wa3YwCX4xRGVjXEfLxZEjq8PyfxZbOsyHML7oq2lipvvLba9Ot0wEdyCqOjnOO5G1sAgPNzlQIAuDyRDgDg8kQ6AIDLE+kAAC5PpAMAuLy7RLqhTyy2vs1rdPGtupdvcNkwD987AMBKN7qcj2aXlVln29UNBbV3DrPW4LdtGwQAukS6zervujqRDgAI3CvSDd1qnP3ZgOAvI1WbrS5etlBdvFoSDyrTn+rYu1vjUfy0a36bmpVXH8weTxsZ7ScA3NmNLpOZhNSq/yxiWbfNOOGtKdyqzfymGNzOlVm6MqXNYlxQCAB0iXSp+q3Fwymr5ZGunBKLV9SqGbeZ3BT5Wbo/1a9HuqBkNmPXmqgDAFpEulT91uI7Rbpua8FSK/u5xXZeFem27QwA3MTdI10w7bQ4k8VPMzNq7ymsPt1iO6fuolZ/l86NVwBY5l6Rrrx1WI105X3G1uPyaXXx2bqqiwdtPoqfTFcfRXRL9nOLTV3/xEP563StT0v4eAQADHGZ5BpEOgAIuEwCAFyeSAcAcHkiHQDA5Yl0/OR3v/80h29SAHgPkY6fHJ7ARDoAWEak4yeHJzCRDgCWuUukW/DVa93vdWvVvK7ZN9W9J3XF64o7My2vVovH+/Nf/mr29LtuzQO9Otnqar6dzWuuPOqqha3vXJwust83LAJcyI1Ofysj3bJGzjaoWBmS3pbqFr8a14zHe/L01urPtGTD3h448O57bZreWoXTfwFu6Eanv6FzfevycLYLhki3ONJ9TzBxYDoDka5b2H0J4A5udBIcujWTjHStBqs3jKYPZnXiZkcXDzoTVw4i3WvZWcnvijue0xUFi+drPmqRLtlgsFmSka51i3N297N88Axvks4KhxYPHgcrKput1uk2mOx8a+3B261V+OhN12UaAfh4NzrfVS8MceVll43Wpagsn66lewGLK2wiiFlBzmvNk70eb1gYT8uViweDHZqlK5NKWT5LOeVaWksFi7d6mMx5QTv56clgwbjz+dnE1tvq9RMXBo0A3MeNToKjkS5/2UhGulaFMtKV161uU5mxtAb1EqS35PxZNX4NpbcyU+4X6VpTUNXK1afJUFVGuurkWdxUvoetoBk3sjLSDa29PESDwuC9020E4D5udBLMJ6GgZibSPWsfsB2KdPkubXsZiyfk4hm7rSJdN7dtEumGpq+qhdWbjOXj7ixdt0srI92aku72yU8rxgde8m3VKuy+BHAHNzoJtkJV/N/9BZEun8m6kS4/S7fJ9Ww0xsWRLp/eFhTmI111F6+MdPlQNXTjNdPUgrUnh9Bqf3Gkqxbm33Gjx7lIB9zcjU6C0zt6s8Jqtdbj6SLVwtmC3Xam5fnFgyFssoke7U8ePCafighq5gunL7WexuVl4feS6vaZ3vGsPv558bv/1d9dq1arLjItzy8+W1d1wda4ys5XC8u4lqmZ7Hx12XJ3lLu4WxgcumX5Jm8NgPNzvtthm+52Y3Rvrfub17XThorvM3Ie13oDAqzhfLfPZm1PJ5zZ4QnsKpHuGc6WAcD7XSxzsKvDE9iFIh0AnIpIx08OT2AiHQAsI9Kxr8NTnZgIwB2IdOzr8AQm0nFpj19kz9KZmsnWymrBgtOX4moth29k+AzeS+zr8AQm0nFC1RzTCjcbprpXhThUlS/FlYdG8f3B7Cmw3l3eS/nPn+Y/rDr0mday2fJrtxYPbfOam2/51897Ule8rrgzj6/fV1xWqw4z/wHYoc/JDn2r3JChPrzzCClf6lZutdB6x5WLxGuJFwnaaQ65l+eCCa1ZqMrXDFZdrVPOvQ3F0GpNs3Swqxu9l5Jn251qVuvPrjfvH+kblCHpbalu8atxzdZI9wtJmb/fsN6BX8hSfSOUD16Pp//GheXi03xWVkh2qbv2znhz2WhZSevVBRGqle2qdYaymhgHe7jR+0qkO4RIt6Zmtf4dIl3wTimfthopny6LdHFh96V5zfRc17I5tsza8/ErmJ97tZNc79BsIrDAjd5Ij8lPt2bcQrfN1oqSkS5uc3Z9avWn22BZXr3gdTdmXDmIdK9lZyW/K+54TlcULJ6v+ahFumSDrZG2IlHy73RVa1ZbbkW6uM3gT4ol//BXq3z2F8DitbcOp9njR/udUj5tNVI+rR7hcWvVZqtvpbhLPxWO3L5c88mDVrXMesvKQZvVpvLTh8BWbvS+Cs74Qc148Xxh62kZiVa2GYwuWLC85nW3UlIQs4Kc15onez3esDCelisXb4209XdXy8f5wtbTavxa02ar//GCZapLrr08MmdvhP0i3ezfoLXqe7MsDBqpNDuS52Yvjd4wrZaXQa1VLWihuq5MpDM/B7u60dtpZaR7vdS68MxSUfXUv+bKVL2QVBtZGemGtkPrCvcSpLfk/Fk1fg2lt+nPmyPd66Vq6HkWqag109ZdUTx1l+ntykg3tPbgyJzlre6hGzRSPp02Xj3mW4sEhUEjlWYHI93r1U3y3PTV6dM18asVEN92Kxl4udHbaX2kK0/oydN9q+XRK9Piku7aRyNdXjwhF8/YbRXpurlt10iXnL6KE2F3RfGU2LKS7tqTE3LdVHfmSNct7L70pdp4pIsrjP6OWjXSBasY6tuC1kQ62NCN3k6tBBNHonx6y6SixVemfJutpeKn74903Zy3Mr0tKMxHuuphs/Ie69CN13I7b3jjNb/2BSNa8I5L/qcljnHTx0Gk2+p/a/U6K/Jc/lMIQ60FISxTZ1aYj3TdmsACN3o7PSY/s8JWtWrlaXm12rQ8s2zQ1Uzngw50a85Kkt1bvNkf7U8ePCafighq5gunL7WexuVl4feS6mEzu20af/gguMGaX7bc1PHiQZuzl7o1y/vI1e5Vly033WyzB4dx690RF5ZPH8Wbd9aBuDDzhn2Vf3k6GOmSH1BItlatkP8QwyYTbyId7MrbiX217m9e1+GblKv4EihH8tzQBxSm5aP3SfO/Rde6mfua9otrjt4gBhbwRmJfhycwkQ6AOxDp2NfhCUykA+AORDr2dXgCE+kAuAORDgDg8kQ6gAtY+QmDzAdR42qtBX24AU7CWxHgFOJPxcbBq1uSj3T5T6H6LhI4lbu8D1tfKBVUDr6GasMuvWFFe2/Vk3R+185s2+Z++33b1oJvsNtvLfut6CT7qLnGkS/yLYPXJpFudLpOkoNTudEbcvS8/Ibz+HQVe69u8/bXd36/Lp0hYr5/+Dt5Q8aK/57YgcN55z5KRrry+95ai2ciXZkOW/dSfbEcnN+N3ocnj3SXW9f6Bk+YMt/p/D387s2R7lTrets+ynwRcfX2aNBCPn7l5/My3QaOcqM35OhtlFk+aC0eF1YbKVfRbfP1dPYg06WgZrCJMhsqWG/Qh506X+6y1qYLVvRasDWQoMHRY6zame4Gaa1ov34O/TGxVmHw98SejT8L26o5/WtjQ11acHt3231UtvlTYS7SxX+VIdNmdS3lDdz8splqwHvc6A05OzsP1X9OrvTTl6ptxq/OKlSvxK3Hi7uUHPKyrZoZZrJLweKzYQ7t4viymllR9Wqd2e/J3g7tzWBFe/SzzEmzf5+NO6fxq7MKQc4rHy/uUjmcBfso2IzLNnImz81Kygy3MtKVbVZXUb1LC5zEjd6Qe0S610vxtXNaJ1Mz2ed8l/JDrvZzwbYNskU8otZWqjab3MWtpfIrGrq0J7fbtgfYfv3M5KfXS7NZsbKF6lTZUA4rM1m+S9XFR/dRuRmTb+3mWsYjXVmSvPFabSH+4MXQSoED3egNuSDflE/LK24rlsWZIFkY93m0S+/ctpnxZkJeMMw1m666lVZGumcjuWZ6u2Bvjm7hxf1MRrogwAWtJQuXRbpuUly2j4L9MqucDfeDkS55mzU/bzf0idfFv3gH7O1G78bgf9jd+s/GFTd/il9Zs1o536XuSrfant2ncZeCV8thBolwKDtm8ujiS/vbDrD9+rn+xmurtQU1q5WX3Xh9PRjdR8H2XPAuS+a5sjD+eES+2Wn54kgn2MEZ3Oh9+Jj8zAqDmq9L7OyKO8sWs5bLFZWF1Tqtl1qryHepNdhtt+frpXzNzFYqhxksuKB8urpZ/8tqrcfBjnvDAbZHP8ubpNMH06fVytPCarNBndZLrVXkuzSr0xr70JGcL6y0ORLp8l8jsjjSZW68lp+oEOngDLwPd9im4dTaHRj1rltg5Yre1s/FtzsPN82+rU23eCN/eWlR8Oq+OtpCZpYu/wt2wFG8D/fZrI3/oH+2e476kC2wckVv62cwA3dmQ7Nuh29kgO+cbgAALk+kAwC4PJEOAODyRDoAzijzqYvkVx8n/4ra7NXMR4DhPByjAD+afprhz372s9e/Z3ZgP5d9+GPDz/k+05HuWftgb9yT8k9rvH8Lw5B7HaOTb5U6fuC7dmbDNmdf7vWGTy+eZAe9YYwnGalDsdrV/aLSn/3sZxs2u76f5T5qHQ/VDwKPrauX59Z8/V4ydXUjnVk6LupGx+j01LPwP5dbX/BeDZ7huh5Y/wVj+aVWbpOTb8mykycZpkNxNva9p762anmTPBektOrjNQdwJtLlF39NpA3Fr/zEmxjHtdzoeF1/rdrvOrpH4xtaPx2yINKt36Sn5VBcbL9D8c2jPtX93NFIt3jTDd1yzbSWnKWb5rzqVyiXNU3UcUX3OkDLM9frf6izGw2zW1GPrztQlCQAABKZSURBVD+tRuKacX9mLUwfBCt6LdgaSNBgOcyW1t/iDP40U/ePMlW3xtBGno0ov+UfxU+75rfH49v0weylV+G0ZrW+Q/Hkh2J3E83ulk6ffn9cfbVa3iqMl62uaBPlvpg9jo+l6qarF6YjXTJOVdNYc5jjgUyG41pud7yW15jycbdCZvHpv0FnWo+7J9l4RdXrZWuY3YtZ6w9llo9nV9Bq5e4OSm7k7v7axCy3zR6UhdN/uyN1KAbjrdrvUMwcObMcFhQ+G4Esufgs4cUrWi+zi4NNlHzTrZmiS/4ps+o83KxyMiman+OKbnqYVv8bOquQ+c9o9T+vm1xHW/WTK8pfhrudfDamRlrX0bjC0K7JdD656YK91ttH9fQ2NX01H+lanXcoBvY7FNdEutbcW2bxWSOjNTdx8kjXnXhb9lHWoV6JdFzCTQ/T7nW0rFatEyy1+XW0df1bfB19NuJCqXoVvG6kGxJMyFVrbh7pquNyKLYKd410z9rHEVrpKh/p8hNy1QrrnSrSjX7itZXP4liWmc/rdh7O5kaHaXBuGj2jxcGienmL51qGLtiZEDA0NTKrWZZveB3tZrutIt1W2a4b6crH3TznUMzsrPcfipljJo50C2bpVhZWJfPx0D4KdlNqFbk8N1pnOvHWvUka5L+g2XxX4XA3Okwfk5/ypXzNVuVZhde/swfdtWTKq9fsVrXW4/JptZ/BJxuqv5M+/bX02aU0k+fisZdPM0NYccz8dGu1+nmI8jMTr38dimW1YMdl9uPeh2LysKlmtczHIGblrVu301fjmvExlhlLdcsHu6NaM9OBvSPdaOXkLJ1Ix7U4TH/73G5G51pm5+vD+8PzrjviPIfiZ2z/t40iWNGXfboozw19w1yyzVez8VNfYsJF3foArf6n81ZsgZOwI2wBgJWcQAEALk+kAwC4PJEOAODyRDoAgMsT6QAALu8ukS7/Ybr8J++GPqAXf8/T2T7rd7b+AACxG122h+LX5jWr9dd/HdcewevV5nm6BADEbnT1PXmk23tQb2tTpAOA97vR1Td/izP4EzfBzdO4ZrXl1nzYbPHX47IwM6L8Hd6g2vouiXoAsJ8bXWVnUSxZM148X9h6Wo2J1TYz7W++oU7SJQAgdqOr78pI93qpG2Xiua7q00ykWzCQan+6i+Qj3eIuAQDbutHVd32kK9NMN+vELa+cDuwOZP2GOkmXAIDYja6+3buH3ZprCjNPF7SZyZFrNtRJugQAxG500a3eeazeG23dpizLW3czh5YNulo+zQxh8620SZc27CQAMOMqy5uIdACwH1dZAIDLE+kAAC5PpAMAuDyRDgDg8kQ6TuTxi0esu3hmFUP9ybwU93DxcJZtwOQQZv1/z/4FYD9O5bxVK/SUr2bSyaxkNFGVuWooUJbdzowurtx9aWgL51cR9xyA87vLKTv/5W3Jr46bLbLV2t82zEM6380N07hTZqllkW5ZD4cmsbqRbmiWbvEoFoTRZbsMgBO60fk6n0tm35q769o3j3p7ZMetOp+MdLMUskmkSyaqZbd9MxNvyQrJOt0FM/OdyWnLZZ0B4M1udL4W6Y7tfObW3iyItLJdWWfBvFTmJml3vdUhVEex+fxZtfPJlDa0FqkO4BJudLJ+TH66NVuPZ4u3GizX9ZjcyS3rxF16FD/dzpfV3tn5ag+Tka6a5Da5gZicpavWb7WZXHt+kSAOzgpfj1vLBittTStm9hEA53Sjk/UszcQ1W7GmunjraZmfRnuybJjlig7vfDIrlIEmX3+brTc+fZVMiplqZQeqySwIZKNzgSIdwMe40cl6KNKVj4N5qWQqWtCT6qqv1fkfa45HurIkuAEax5f8rc9WSutO6a0fabU8mHiLk1b+1QWdB+CEbnSyXh/pMvVfJUFyWpaK1gzz8M6PBp3kbdZlJcGri6evXlkwOfzNI92C5BoPObkBATiJG52sg+mrZM1qhe7TePFM6tpkmAd2Pj/3U40pwauZZmcxcRZxVmad7hRXq6lM5W5/ko0kV2GKDuDSbnS+rt55rM5IvQpn9VuLB+XdNqt9WD/GYzs/36QjkW7ZVFNQGN8ejduM728umKVbEOnKDPpaV9C90duypugArs75eodtuujW5Els0vkvjYzM/Sz7DbC4hWCWrjXNVk1R+bm6VibrhtRqTxbugsSW7HZJngO4EKfsfTZrMZt1IZfu/CeJYx8ATLlaAABcnkgHAHB5Ih0AwOWJdOxu2UcEpotnVjHUn8xLcQ8XD2fZBkwOwYcbAG7LSZ8NxB9rjXNGt2Q0UZW5aihQlt3OjC7zGdU1GSuZ1ZKbbsNdD8BJ3OXknv8I5/Q72MoFW43E7b//A6Tv7Gc3NwRfI1JdfCiXtFaUr9wd1yazdGu+jmQ0jC7bZQBc2o3O7PmwMot0C9ovlzrPd4Js3s9kpGt959mySPcczDoL7pNmJt6SFZJ1ugtm5juT05bLOgPAad3ozC7S7dHPzK29WRBpZbuyTiZ+ZSbekrN007WUQ6iOYvP5s2rnkyltaC1SHcCHudFp/TH56dZ8FpGuteys2cfXn7LNeO2P4ieuWba8Xz+rnUlGumqSWxmAFiSqzPzcgqwzNI1X7cMsTWZm5uJhju4jAK7uRqf1MrjENWeRrrpgq81WosqsfXREB/YzmRXKQJOvP7r2NQ1OKycnCDPVyg5Uk1kQyBYk1wW7CYBLu9FpfSjStSar1kSlzNofxU93RJtHuuRWei6KdGVJcAO0m6jyDS5oNm4zOdJqedDzOGnlX13QeQAu7Uan9bGwUstJZclOUWloRBeKdMnbrMmo9IY7kq8smBz+5pEumKKL5ztbQ+52FYCLutFpvRpWWjNhW0W66k3MrSLdsf3Mz/1UY0rwarLZ2atBndGs053iajU12oc1jawZpjwH8HludGav3s3MR7rW/dC4fFZn9niTQb2tn/OYOBLplk01xYWvlss6cZvx/c0Fs3QLIt1s7K/HwR3huP3qq6boAO7DmZ2sL/FuMHhFzSamxKphpVXYmmarpqj8XF0rk3VDarUnC3dBbrYy7pI8B/CRnNzhreLYBwDLuK4AAFyeSAcAcHkiHQDA5Yl0AACXJ9IBAFyeSAcAcHkiHQDA5Yl0AACXJ9IBAFyeSAcAcHkiHQDA5Yl0AACXJ9IBAFyeSAcAcHkiHQDA5Yl0AACXJ9IBAFyeSAcAcHkiHQDA5Yl0cLDHLwbeht8rl4s8fvGIbdgHAE7IeZwNPB4feyAtG1o1Ic0KX08XRLqgtWqD3RKRDuDqbnceP3n4eDweyR4+ip8De3L4dtt1mKMDzOS5ZzrSJefepq2VFUQ6gI/nPH46+QAxrblHrloW6S6X8A6MdJk7pMns9boh28p5y5oF4Cqcx09nWaQ7qidlnc+LdEODGp2iay3SejWOdK/HrWxX1hn9rTsAzulGp+/yBmVw4zIurDaSWfVo5e6IygffH6/p/NAwu9tz+rTcDsHaV+7l/YbZKRz5Lbpgkemr07AV/C5dNcklJ/8AuLrbndbL6/rs32cRU1oPgsdb9TBuMwglmT6vLGz1MC5ZvKLFm26nYdY7kJuiG6owy3DJj0d0U6NIB/Bhbndaz0S610uZeFTNVeVKkzXL9jM1uymzO8nUzTqtzmciXXULj65owc7ddZj1DoxEuuRNz2qkG/1Ma/LG6+gGB+A8bncST0a6IMAFrW3ew3z4ixdfn3XyfVgZ6bbadHsPs15t/1m66oNZ4WjgS/YTgDO73Uk8E+lWpqINezibQErWfE9hvEmD8gVrzyaqfYa5a57r1pl9lLU1V1f91brg1WVdBeC0bnQSL2+rTR88v0aHsvK0sNrsHv2cFQbDmQ6hfDzU+fzYXy9VhxBXqw4z6NLo1ttwmK21z6vtGemqj1ufhOjeVBXpAD6Pk3h6S+0wIfcxMhtkTUo759C+HBIjISkfv7q/D9ddV76mSAdwaU7iIxurPVPF0EazJQFgW66pAACXJ9IBAFyeSAcAcHkiHQDA5Yl0AACXJ9Idzwc/AYCVhInGdnl8O7wPAABJIl1ju4h0AMB13CjSPR7fvge114Np+avk9bQsDB4HD8Iuzb9xt/pXqlqVZ/Xjmk93eAHgc93rGl/GrFm2qz7u1izbnGa+RK8qfylr+u+sTlnY+mNlMhwA3MS9LvnVoFbOybVqdh9nXq31qh/pXi/N/sZ82UIwzwcAfKp7XfLj+JWveUikCwJc0BoAcAf3uvwvCGrVB++PdN1sV21NvAOAm7jRJb96g3VaXq1fLZk9qH66Imh50uD8Jun0wfRptfK0sNpsubrD9wIAsAfX+AsbnZAT6QDgU7nGX5uPQQAAT5EOAOADiHQAAJcn0gEAXJ5IBwBweSeNdH7lHwAg77yxSaQDAEg6b2wS6QAAks4bm0Q6AICk88YmkQ4AIOnUsUmqAwDIOG9mkucAAJLOG5tEOgCApPPGJpEOACDpvLFJpAMASDppbPLXIwAA8sQmAIDLE+kAAC5PpAMAuDyRDgDg8kQ6AIDLE+l6G8gHb20EADi9u1yqH49vj8e38aV+3D4//+WvZg4ZxVHrfUp1AHBun3CdTma1NZHu+TVO7R2tDoxumU0BAJzNJ1ynd4p0sxDzzph1wkhXbhAA4DzOe5H+fqt0dsN0VjKtM0tsZfn3B/k7sK1IN33wugk7uxtbvUU7K6neyW3d3m3d8K0uXvYnGOP0D3VMn5Z/wEOkA4DTOulFehbjgsJnbfqttXi1qXYf5pGumrRmD1qPly01MytvtVltPx7gNNVVh18tAQBO4qQX6SByVafuMovHi9Tqd2bpXk+DpDWrVk6qVZdaGem67bwGOP2ZlXc3CABwHie9SLciV3fGLlh8q0g3k490ceEhka5VLtIBwLWc9CK97MZrXHM00j0Tn3jd+8ZrHBY3jHTdG6/yHACc2Xmv090PPZQfmwgWnz6tttzoQ/S9dLMH3U8zBNVan3uo1sx85KLVh3KA5ccjyvKnSAcA5+Y63dtAe0aZzIdSz0CeA4CTc6k+TGYWbVf/4N//w7/2L//63/hXf/PXf/hNq+Q//J//dPiGAgC6RLqb+s//97/+nX/zd3/9h9/8k7/4p//oz//x84+//Wf/5Z+XJX/+v//j4V0FALpEupv6d//rL/7b//vvzz/+9td/+M3f+td/++/927//V/7FXy1L/sf//5+HdxUA6BLpAAAuT6QDALi8s0e61tfeAgDwcva0JM8BAHSdPTCJdAAAXWcPTCIdAEDX2QOTSAcA0HXqwCTPAQBknD0zSXUAAF1nD0wiHQBA19kDk0gHANB19sAk0gEAdJ09MPnrEQAAXdISAMDliXQAAJcn0gEAXJ5IBwBweSIdAMDliXQAAJd3u0j3SV+J8nh8+65bCAB8ts/JN7dVTW8iHQDcikh3eSIdAHCjSPf4009ZUv6Niriw2khm1d3Kr3um05unrcevkmo71W4cvhcAgD3c7hpfprTZv7M6ZWH11bLlFT38EuBmD55FXDNLBwCIdJVI93ppOqPWinS5ubfsLN2zkd5EOgAgINLVI10Q4ILWNuqhSAcAjBHphm+8tlrb8MZr+XiT36UDAD7VjSJdeetz+uD5dRKuep+0ets0cy91pJM/favc7Bvmyk9OvCqU1RpfWXej3Q0At+Ian95SO0zIHTgEAOCTuMaPbKxNJ+QAALYinQAAXJ5IBwBweSIdAMDliXQAAJd30kjnUwgAAHnnjU0iHQBA0nljk0gHAJB03tgk0gEAJJ03Nol0AABJp45NUh0AQMZ5M5M8BwCQdN7YJNIBACSdNzaJdAAASeeNTSIdAEDSSWOTvx4BAJAnNgEAXJ5IBwBweSIdAMDliXQAAJcn0gEAXJ5IBwBweSLdDtv08e27biEAwCY+IdKdMydVe3XOrgIAVyfSvbVX5+wqAHB1J410r3uUs5uVs9uXr6dlYfA4eDDUn9bjV0m1nVrhSfcCAHAV5w0TcUhqPe7WrP6KW6udbs2gG2bpAIC3OXWkK0vKOblWze7jzKvdmiIdAHAGF4t0C2qKdADAx7tqpIsDVutX3PaLdGt+lw4AYKWTRrrqDdZpebV+tWT2oPrpiqDlbs14ReW6al096V4AAK5CmDieSAcArCRMAABcnkgHAHB5Ih0AwOWJdAAAlyfSAQBc3gaR7vF4+MwmAMCBtoliIh0AwIFEOgCAyxPpAAAuT6QDALi8zaKYVAcAcBSzdAAAlyfSAQBcnkgHAHB5Ih0AwOX56xEAAJcnigEAXJ5IBwBweSIdAMDliXQAAJcn0gEAXJ5IBwBweSIdAMDliXQAAJcn0gEAXJ5IBwBweSIdAMDliXQAAJcn0gEAXJ5IBwBweX8JQJNzMP+ke+UAAAAASUVORK5CYII=" alt="" />
注意:
建议image流直接获取条码生成的图片流,即从内存读取。
此外,RDLC图片属性的大小,要设置为原始大小(第一个选项),否则部分扫描枪不能扫描,因为条码图片被自动拉升而变形。
如果使用图片文件,可能导致不清晰,如下
Image img = Image.FromFile(path);