Open AccessA Pipeline-based Low Complexity Dual Thresholds and Multiresolution Mouth Detection Method
Author(s) -
Jie Lin,
Changwei Li,
Xi Lan,
Jinge Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2218/1/012016
Subject(s) - pipeline (software) , computer science , computer vision , field programmable gate array , artificial intelligence , binary image , rgb color model , image processing , image (mathematics) , binary number , mathematics , computer hardware , arithmetic , programming language
Mouth detection is a basic step in the automatic diagnosis of buccal diseases. This paper proposes a method of using FPGA(Field Prog ram mable Gate Array) to detect the human mouth region in images, which adopts a pipelined design for high-speed operating. Thus, it can be applied to mouth motion detection as well. After an original image is processed regularly by median filtering, color conversion is performed to obtain its corresponding H component, which is used to create a partitioned binary image. Each constituent region of the binary image uses two thresholds for regional processing separately, which results in two binary images: one comprises the mouth and some other regions with a color close to that of the mouth, and the other indicates the position of the mouth. A logical AND is performed on these two binary images to calculate the border of mouth region with reduced resolution, which is then superimposed on the buffered original image to confirm the mouth region eventually. An FPGA-based scheme is presented, which shows the method could detect the whole mouth properly, with a maximum clock speed of 150MHz. In addition, processing an image of 200*200 only consumes 2178 Slice LUTs(Look Up Table), which is a relatively low resource consumption.