CN112446236A - Conversion event linear detection method based on pulse type image sensor - Google Patents

Abstract

A conversion event straight line detection method based on a pulse type image sensor comprises the steps of converting high-speed pulses into event signals with directions, adopting a least square method to parameterize straight lines, calculating liveness and judging whether events belong to straight lines or not. The detection algorithm is suitable for parallel operation, can be applied in real time, and can achieve image detection, identification and tracking accurate to pixel points.

Description

Conversion event linear detection method based on pulse type image sensor

Technical Field

The invention relates to the field of image processing algorithms, in particular to a dynamic object detection method aiming at a pulse type image sensor, namely a conversion event linear detection method based on the pulse type image sensor.

Background

The impulse type high-speed image sensor has great advantages when shooting complex high-speed changing scenes, and can be used for flight detection systems of robots and unmanned aerial vehicles. Extracting straight lines from man-made environments is a fundamental task of machine vision, often used for robotically recognizing paths and various pattern recognition scenarios. The commonly used detection means are classical huffman transform based methods, gradient based methods, statistical based methods. After the address-event sensor appears, an event-based line detection method also appears, a buffer is usually needed to store the whole frame of data, and when the scene changes dramatically to increase the number of events, the invalid time occupies a large amount of resources of the buffer, resulting in low calculation efficiency.

Disclosure of Invention

Aiming at the problems in the prior art, the invention discloses a conversion event straight line detection method based on a pulse type image sensor. The detection algorithm is suitable for parallel operation, can be applied in real time, and can achieve image detection, identification and tracking accurate to pixel points.

A conversion event straight line detection method based on a pulse type image sensor specifically comprises the following steps:

1. converting the high-speed pulse into an event signal with a direction: for a position of [ x_k,y_k]A pixel of (2), taking a small time t_sCounting the number of pulses, t adjacent to it_sThe number of pulses within is subtracted, a trigger event is deemed to be present above a certain threshold, and the sign of the subtraction is retained, so that the high speed pulse signal is converted into a dynamic event signal, denoted e_k=[u_k ^T,t_k,p_k]^TWherein u is_k=[x_k,y_k]^TRepresents the location of the occurrence of the event, t_kRepresenting the time of occurrence of the event, p_kRepresents the polarity of the event, is 1 or-1;

2. and (3) adopting a least square method to realize straight line parameterization: calculating the visual flow of each incoming event, locally approximating a space-time surface described By the incoming event from a normal three-dimensional plane By applying, and fitting the plane By adopting a least square fitting algorithm in a parameterized standard plane Ax + By + t + C =0 to obtain the visual flow of each incoming event

The velocity vector v can be obtained by using the Clamer's rule_k:

Recording the directional event as o_k= [u_k ^T,v_k ^T, t_k,p_k]^TRepresenting an event with a rate;

defining a straight line in two-dimensional space by using a rho-theta parameter by using an event-based iterative least squares fitting straight line method with vertical offsetL ⁽ⁱ⁾(ρ_k ⁽ⁱ⁾,θ_k ⁽ⁱ⁾)，ρ_k ⁽ⁱ⁾Is the distance of the straight line from the origin,θ _k ⁽ⁱ⁾is n_k ⁽ⁱ⁾Angle to the horizontal as shown in fig. 1. Straight lines and time being linked by k, e.g.ρ _k ⁽ⁱ⁾Representing the straight line i at time t_kThe straight line can be expressed as:

3. calculating the liveness and judging whether the event belongs to a straight line: each possible fitting straight line calculated in the last step has corresponding activity A_k ⁽ⁱ⁾At a new event e_kWhen this occurs, the activity is updated with the exponential decay equation:

where Δ t_k=t_k-t_k-1This calculation method makes the activity of the line independentAt their respective rates, the description of each line in an adaptive manner is implemented if the line has a degree of activity A_k ⁽ⁱ⁾If the set threshold is exceeded, thenL ⁽ⁱ⁾Is visible, indicating that a line is present at this location.

One direction event o_kThe criterion determined to belong to a straight line is as follows 1. distance d from the point where the event occurred to the straight line_k ⁽ⁱ⁾Less than threshold d_max(ii) a 2. Straight normal sum n_k ⁽ⁱ⁾Angle therebetweenα _k ⁽ⁱ⁾Must be less than a threshold valueα _maxTo ensure orthogonality of the velocity flow and the straight line; these two principles can be expressed by formula (5)

If this condition is not met, a new line needs to be initialized, the initialization method is as follows:

and judging whether the newly generated line meets the requirement, if so, stopping, otherwise, continuously generating a new line, and circularly judging.

A conversion event straight line detection method based on a pulse type image sensor converts pulse data into event data with directions, so that high-speed pulse data which cannot directly restore a scene can be applied to a high-efficiency and quick straight line fitting detection algorithm, and high-speed detection of line segments is realized; the method adopts a weight exponential decay method for the early events, so that the algorithm can still keep effective under the condition of violent scene change, and the adaptability of the algorithm to high-speed calculation is improved.

Drawings

FIG. 1 is a schematic diagram of the principle of an event-based line detection algorithm.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, a detailed description of the embodiments of the present invention will be given below with reference to examples.

As shown in FIG. 1, a straight line indexed by superscript (i)L ⁽ⁱ⁾ (ρ_k ⁽ⁱ⁾,θ_k ⁽ⁱ⁾) It consists of two features:ρ _k ⁽ⁱ⁾represents the distance of the straight line from the origin,θ _k ⁽ⁱ⁾representative line n_k ⁽ⁱ⁾And the angle to the horizontal. When a new event arrives, two conditions are used to determine which line it belongs to before: (1) point to line distance d of event occurrence_k ⁽ⁱ⁾(2) angle between normal phase of straight line and event directionα _k ⁽ⁱ⁾. The actual operation steps of the line detection are as follows:

1. adjusting data format, arranging data into a striped event form, i.e. o_k= [u_k ^T,v_k ^T, t_k,p_k]^T(k.gtoreq.0);

2. for all direction events o_kLine of sumL ⁽ⁱ⁾Doing the formula according to the formula (4) to calculate the activeness

3. When there is a line satisfying the constraint condition (5):

(1) let i = arg max_j A_k ^(j)The liveness corresponds to a straight line satisfying the constraint condition (5)

(2) Make A a_k ^(j) =A_k ^(j) +1

(3) Update sinθ _k ⁽ⁱ⁾ ，cosθ _k ⁽ⁱ⁾

4. Judging if the activity degree A_k ^(j)If the activity is larger than the activity of the previous line, the line is output, otherwise, a line is updated by the formula (6), and a new loop is developed from the step 2.

Claims (1)

1. A conversion event straight line detection method based on a pulse type image sensor is characterized by comprising the following steps: the method specifically comprises the following steps:

1. converting the high-speed pulse into an event signal with a direction: for a position of [ x_k,y_k]A pixel of (2), taking a small time t_sCounting the number of pulses, t adjacent to it_sThe number of pulses within is subtracted, a trigger event is deemed to be present above a certain threshold, and the sign of the subtraction is retained, so that the high speed pulse signal is converted into a dynamic event signal, denoted e_k=[u_k ^T,t_k,p_k]^TWherein u is_k=[x_k,y_k]^TRepresents the location of the occurrence of the event, t_kRepresenting the time of occurrence of the event, p_kRepresents the polarity of the event, is 1 or-1;

2. and (3) adopting a least square method to realize straight line parameterization: calculating the visual flow of each incoming event, locally approximating a space-time surface described By the incoming event from a normal three-dimensional plane By applying, and fitting the plane By adopting a least square fitting algorithm in a parameterized standard plane Ax + By + t + C =0 to obtain the visual flow of each incoming event

The velocity vector v can be obtained by using the Clamer's rule_k：

Recording the directional event as o_k= [u_k ^T,v_k ^T, t_k,p_k]^TRepresenting an event with a rate;

defining a straight line in two-dimensional space by using a rho-theta parameter by using an event-based iterative least squares fitting straight line method with vertical offsetL ⁽ⁱ⁾(ρ_k ⁽ⁱ⁾,θ_k ⁽ⁱ⁾)，ρ_k ⁽ⁱ⁾Is the distance of the straight line from the origin,θ _k ⁽ⁱ⁾is n_k ⁽ⁱ⁾Angle to the horizontalThe line and time are linked by k, and the line can be expressed as:

3. calculating the liveness and judging whether the event belongs to a straight line: each possible fitting straight line calculated in the last step has corresponding activity A_k ⁽ⁱ⁾At a new event e_kWhen this occurs, the activity is updated with the exponential decay equation:

where Δ t_k=t_k-t_k-1The calculation method makes the activity of the lines independent of their respective speed, and realizes that each line is described by an adaptive method if the activity A of the line_k ⁽ⁱ⁾If the set threshold is exceeded, thenL ⁽ⁱ⁾Is visible, indicating that a line is present at this location;

one direction event o_kThe criterion determined to belong to a straight line is as follows 1. distance d from the point where the event occurred to the straight line_k ⁽ⁱ⁾Less than threshold d_max(ii) a 2. Straight normal sum n_k ⁽ⁱ⁾Angle therebetweenα _k ⁽ⁱ⁾Must be less than a threshold valueα _maxTo ensure orthogonality of the velocity flow and the straight line; these two principles can be expressed by formula (5)

If this condition is not met, a new line needs to be initialized, the initialization method is as follows:

and judging whether the newly generated line meets the requirement, if so, stopping, otherwise, continuously generating a new line, and circularly judging.

Images