Data Flow Implementation of Erosion and Dilation

2021 ◽  
pp. 106-113
Author(s):  
Christina Pacher
Keyword(s):  
Image Processing ◽  
Data Flow ◽  
Control Flow ◽  
Basic Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms

This chapter describes a data flow implementation of the image processing algorithms Erosion and Dilation. Erosion and Dilation are basic image processing algorithms which are used to reduce or increase the size of objects in images, respectively, and which are used in a wide number of image processing applications. The chapter first describes the control flow versions of the algorithms in detail. Subsequently, the translation of these algorithms to the Data Flow paradigm is examined, and the details of the data flow implementation as well as possible optimizations are discussed.

A μc-Si:H P-I-N Imager For 2-D Pattern Recognition

1999 ◽  
Vol 558 ◽  
Author(s):  
J. Martins ◽  
M. Fernandes ◽  
F. Sousa ◽  
P. Louro ◽  
A. MaçArico ◽  
...  
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Image Enhancement ◽  
Image Representation ◽  
Rectangular Grid ◽  
Sensing Element ◽  
Coplanar Electrodes ◽  
Basic Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms

ABSTRACTA TCO/ μc-p-i-n Si:H/AI imager is presented and analyzed. The μc-p-i-n Si:H photodiode acts as a sensing element. Contacts are used as an electrical interface. The image is acquired by a scan-out process. Sampling is performed on a rectangular grid, and the read-out of the photogenerated charges is achieved by measuring simultaneously both transverse photovoltages at the coplanar electrodes. The image representation in gray-tones is obtained by using low level processing algorithms. Basic image processing algorithms are developed for image enhancement and restoration.

scholarly journals Implementation and Performance Testing of Background Subtraction Algorithm on ESP32

2019 ◽  
Vol 6 (2) ◽  
pp. 9-15
Author(s):  
DIDIT ANDRI JATMIKO ◽  
Salita Ulitia Prini
Keyword(s):  
Image Processing ◽  
Low Power ◽  
Background Subtraction ◽  
Performance Testing ◽  
Low Complexity ◽  
Pixel Image ◽  
Basic Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
And Performance

This paper describes the background subtraction algorithm and its performance in low power processing units, this algorithm has low complexity and can be used to detect objects so that it has the potential to be applied to security cameras. This study has succeeded in applying basic image processing algorithms to detect and track objects, such as background subtraction in the ESP32 module. The ESP32 module equipped with Xtensa® 32-bit LX6 microprocessor running at 240MHz can process 10000 times background subtraction algorithms in ~ 2000ms using 80x60 pixel image input. Background Subtraction; Embedded; ESP32; Image Processing; Microcontroller; Object Detection;

scholarly journals Linking of Cell Tracks using Segmentation

2019 ◽  
Vol 9 (1) ◽  
pp. 3020-3026
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Literature Review ◽  
Parallel Algorithms ◽  
Digital Image ◽  
Important Task ◽  
Basic Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms

In maximum of image processing algorithms Segmentation is a key technique. It splits a digital image into several regions so as to examine them. Once segmentation is done, linking of frames is additionally is very important task. Several image segmentation techniques are developed by the researchers so as to form pictures swish and simple to judge. It is troublesome to process parallel algorithms in serial processors. This paper presents a literature review of basic image segmentation techniques, linking algorithms and want to process in hardware tools.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

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