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A CMOS imaging device for visual prosthetics using on-pixel gray-scale erosion for edge detection.

机译:一种用于视觉修复的CMOS成像设备,其使用像素上的灰度腐蚀来进行边缘检测。

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摘要

This thesis proposes a new design for on-pixel implementation of gray-scale morphology, aimed at visual prosthetics. These implants rely on providing the patient with a sketch or a realistic edge representation of the real world. Edge detection can be carried out using classical algorithms or mathematical morphology.; Threshold decomposition of gray-scale images allows for the simplification of grayscale mathematical morphology into binary morphology. Binary morphology can be implemented on pixel by using AND, OR and inverter gates. Gray-scale morphology on the other hand, needs more complex operations. By using threshold decomposition, these operations can be carried out in terms of binary morphology. To carry out threshold decomposition in hardware, a specialized system is needed to decompose the gray-scale image into M binary images, where M is the largest value a pixel can have in the gray-scale image.; This thesis proposes a new method for gray-scale mathematical morphology, called bitwise decomposition of gray-scale images. The proposed method reduces the number of binary images produced from M to N, where N is the number of bits representing the pixels of a gray-scale image. Binary erosion can then be carried out on the generated binary images, and the eroded gray-scale image reconstructed.; Erosion was chosen for edge detection since it produces correctly placed edges in the edge image. Once the gray-scale eroded image is available, it is used in morphological edge detection, where the results are comparable with classical algorithms. Once testing the new method in software is complete, the method is implemented in hardware.; A pixel employing the method of bitwise decomposition is designed in 0.13 mum technology. The pixel is then placed in three array structures; a 4x4, 8x8 and a 16x16 array. All arrays produced correct results as expected.; Layout of the pixel is drawn and tested using the layout-level simulations. The results snatch that of schematic-level tests. The fill factor of the pixel came to 22%, and the device has a dynamic range of 46 dB. Pixel dimension is 17x17 mu m, and transistor count 107. An analog to digital converters resolution is 8-bits and has a conversion time of 40 musec. The power dissipation of the 16x16 is 0.38 mW.
机译:本文针对视觉修复提出了一种新的像素上实现灰度形态的设计。这些植入物依赖于为患者提供现实世界的草图或逼真的边缘表示。边缘检测可以使用经典算法或数学形态进行。灰度图像的阈值分解允许将灰度数学形态简化为二进制形态。二进制形态可以通过使用AND,OR和反相器门在像素上实现。另一方面,灰度形态需要更复杂的操作。通过使用阈值分解,可以根据二进制形态来执行这些操作。为了在硬件中进行阈值分解,需要专门的系统将灰度图像分解为M个二进制图像,其中M是像素在灰度图像中可以具有的最大值。本文提出了一种新的灰度数学形态学方法,即灰度图像的按位分解。所提出的方法将由M生成的二进制图像的数量减少到N,其中N是代表灰度图像像素的位数。然后可以对生成的二进制图像进行二进制腐蚀,并重建侵蚀的灰度图像。选择侵蚀进行边缘检测是因为它会在边缘图像中正确放置边缘。一旦灰度侵蚀图像可用,就将其用于形态学边缘检测,其结果与经典算法相当。一旦在软件中测试了新方法,就可以在硬件中实现该方法。在0.13μm技术中设计了采用按位分解方法的像素。然后,将像素放置在三个阵列结构中。 4x4、8x8和16x16阵列。所有阵列均产生预期的正确结果。使用布局级模拟绘制并测试像素的布局。结果抢走了原理图级测试的结果。像素的填充率达到22%,并且该器件的动态范围为46 dB。像素尺寸为17x17微米,晶体管数为107。模数转换器的分辨率为8位,转换时间为40毫秒。 16x16的功耗为0.38 mW。

著录项

  • 作者

    Jabakhanji, Duha.;

  • 作者单位

    Carleton University (Canada).;

  • 授予单位 Carleton University (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.A.Sc.
  • 年度 2007
  • 页码 170 p.
  • 总页数 170
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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